AI startup 1001 has successfully secured $30 million in funding from a range of investors, including the US-based venture capital firm Lux Capital and the Saudi sovereign wealth fund’s Sanabil unit. The company aims to leverage artificial intelligence to enhance the operational efficiency of aviation, ports, and energy infrastructure throughout the region.

The funding round, primarily led by Lux Capital, also saw contributions from 9Yards, Hanabi, and Sanabil, with General Catalyst and CIV among the participating investors.

In a conversation with Semafor, Bilal Abu-Ghazaleh, the founder and CEO of 1001, emphasized that the ongoing conflict in Iran had “zero impact” on their fundraising endeavors. In fact, he noted that the war has prompted many enterprises to explore AI solutions that can help construct new supply chains and reduce operational costs, especially as the region aims to lessen its dependence on the Strait of Hormuz for trade.

1001 intends to collaborate closely with airlines, port operators, and shipping companies across the Gulf. The startup plans to temporarily place its engineers within these organizations to address immediate operational challenges and innovate new AI-driven solutions. Abu-Ghazaleh pointed out that regional governments are actively encouraging businesses to embrace technological advancements, which opens up opportunities for startups focused on practical AI applications.

“The Middle East may not lead in cutting-edge AI models, but in the realm of applied AI, there is significant potential,” added Abu-Ghazaleh, highlighting a promising landscape for innovation within the region.

US investors spearhead $30M investment round for Gulf AI company 1001

A sleek Gulf co-working space bathed in warm natural light: a diverse group of adult investors in business attire shakes hands across a polished wooden table with a Gulf AI founder; on the table sits a large golden check reading “$30M Funding”; behind them a stylized “1001” logo is etched on a glass wall; a US flag stands prominently in the corner; through floor-to-ceiling windows, a modern city skyline sparkles under a clear sky.

Exclusive / US investors lead $30M funding for Gulf AI startup 1001 - Semafor

- AI startup 1001 raised $30 million to enhance regional aviation, ports, and energy efficiency.  
- The funding was led by Lux Capital, with participation from various other investors.  
- The Iran war spurred interest in AI for new supply chains and cost reduction.  

AI startup 1001 has raised $30 million from investors including US venture firm Lux Capital and Saudi sovereign wealth fund unit Sanabil, as it looks to use AI to boost the efficiency of the regionâs aviation, ports, and energy infrastructure.

The funding round was led by Lux, with participation from 9Yards, Hanabi, and Sanabil. General Catalyst and CIV are also investors in the company.

The Iran war had âzero impactâ on fundraising discussions, Bilal Abu-Ghazaleh, founder and CEO of 1001, told Semafor. The conflict has also driven more firms to look for ways to use AI to help build new supply chains and lower costs at a time when the region is looking to diversify away from a reliance on the Strait of Hormuz, he said.

1001 plans to work with the Gulfâs airlines, port operators, and shipping companies, temporarily embedding engineers in their offices to help fix operational problems and develop new AI-enabled products. Abu-Ghazaleh said governments across the region are pushing businesses to adopt the technology, creating an opening for startups that are focused on practical applications.

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âThe Middle East is not necessarily going to compete in terms of frontier models, but in terms of applied AI, itâs a bit of a green space,â said Abu-Ghazaleh.

US investors lead $30M funding for Gulf AI startup 1001

The advent of artificial intelligence has introduced remarkable changes, particularly in the realm of enterprise IT. According to a prediction by market research firm IDC, companies that have traditionally been hesitant and selective about their tech investments are projected to spend around $4.25 trillion on technology by 2026, largely driven by advancements in AI.

A recent survey conducted by the venture capital firm Madrona indicates that 74% of the 150 enterprise IT professionals questioned expect to increase their AI budgets over the next year, while the remaining participants aim to maintain their current spending levels. Yet, despite this optimism, less than half of these enterprises report that their AI pilot projects transition into full-scale production.

This represents a significant improvement compared to findings from MIT last year, which revealed that a staggering 95% of enterprise AI initiatives failed to deliver a return on investment. Although having less than half of projects succeed sets a low standard, it is certainly an improvement from the previously dismal 5% success rate.

Moreover, Madrona's research highlights that when companies do implement AI technology, they frequently reassess their partnerships with AI vendors. An impressive 77% of firms conduct these evaluations every six months or even continually. This trend fosters a “fast in, fast out” environment that starkly contrasts with traditional enterprise software as a service (SaaS), where lengthy contracts usually create a barrier to switching providers. As noted in the report, “In enterprise AI, switching costs are lower, and the re-evaluation cadence is relentless.”

This trend has significant implications for the rapidly increasing annual recurring revenue (ARR) figures that many startups currently report. The initial boom in AI spending by enterprises was fueled by trial budgets, and this year was anticipated as a turning point where big clients would start making long-term commitments to AI startups. These enterprise contracts are crucial for many AI businesses, enabling them to showcase impressive revenue growth, particularly the phenomenon where startups jump from $0 to $10 million in just three months.

However, an unprecedented challenge has emerged: enterprise revenue remains precarious even after a startup's AI solution moves beyond the pilot stage and is adopted by a company.

One contributing factor is that many AI startups are still struggling to establish effective pricing strategies for their offerings tailored to enterprises. Research from VC firm Andreessen Horowitz, which surveyed 50 technical AI buyers, found that a majority would prefer AI fees to be linked to results or completed work rather than usage metrics, such as the number of tokens utilized.

Adopting a pricing model based on consumption, like that of traditional SaaS, poses a challenge. Once a company identifies a need for tools like email, HR software, or cloud storage, their decision is mostly influenced by employee numbers or data volume. In contrast, pricing AI in relation to tangible outputs—such as reports processed, tickets resolved, or leads generated—demonstrates the product's value more effectively, creating a beneficial economic relationship for both the startup and client, as stated by a16z partners Tugce Erten and Sarah Wang.

Ultimately, these dynamics suggest that AI has initiated a new phase of experimentation in enterprise environments. This shift may present opportunities for startups, as enterprises seem increasingly open to testing new technologies. Yet, it remains uncertain whether and when these organizations will revert to their traditional long-term purchasing patterns.

New research indicates that startup ARR is more vulnerable than ever.

A moody, dimly lit startup office at night. At the center, a large neon “ARR” sign sputters and cracks, glowing red and orange as streams of binary code pour out like leaking data. On the floor beneath, a shattered padlock and scattered security audit reports lie in disarray. In the shadows, a lone silhouetted entrepreneur stands, shoulders slumped, staring at the damaged sign. Overall dark theme with dramatic shadows and warm accent lights to highlight the breach.

Startup ARR is less secure than ever, new research shows - TechCrunch

- Companies are projected to spend $4.25 trillion on technology by 2026, driven by AI.  
- 74% of IT professionals plan to expand AI budgets, despite low pilot success rates.  
- Enterprises reevaluate AI vendors frequently, affecting long-term commitments and revenue stability.  

AI has ushered in a lot of never-happened-before moments, but one of the most transformative is its impact on enterprise IT. Companies that have historically been cautious and committed long-term to what they buy are on pace to spend $4.25 trillion on technology in 2026, market researcher IDC predicts. It’s almost all driven by AI.

New research from venture capital firm Madrona shows that 74% of 150 enterprise IT professionals it surveyed plan to expand their AI budgets in the next 12 months, and the rest plan to hold spending steady. Yet these same enterprises say that fewer than half of their AI pilots ever make it into full production.

That’s actually an improvement. Last year, MIT famously reported that 95% of enterprise AI projects had failed in terms of ROI. Fewer than half succeeding is a pretty low bar, but it’s better than a 5% success rate.

But the most telling finding from Madrona’s report is that, even when an enterprise does roll out the AI tech, it doesn’t commit to it long term.

Some 77% of enterprises reevaluate their AI vendors every six months or even on a rolling basis. “This creates a ‘fast in, fast out’ dynamic that is fundamentally different from traditional enterprise SaaS, where multi-year contracts provided a moat of inertia,” Madrona writes in the report. “In enterprise AI, switching costs are lower and the re-evaluation cadence is relentless.”

This has widespread implications for all those fast-growing annual recurring revenue (ARR) numbers startups report. Enterprise trial budgets are what fueled the initial AI boom of 2025. This year was supposed to be the year these big customers settled in and started committing long term to AI startups. Enterprise contracts are what allow so many AI startups to claim astronomically fast revenue growth — think the phenomenon of startups going from $0-$10 million in three months.

Yet, for the first time ever, enterprise revenue remains insecure, even after a startup’s AI product graduates out of a pilot phase and gets adopted by a company.

Part of the issue is that many AI startups haven’t fully landed on a good way to price their AI wares for enterprises. New research from VC firm Andreessen Horowitz that surveyed 50 technical AI buyers found that more than half of them want AI fees tied to the work produced or other outcomes, rather than to usage like the number of tokens consumed.

Charging for usage like tokens is basically a SaaS-era business model. Once an enterprise knows it needs email, or HR software, or cloud storage, it’s merely a matter of how many employees or how much data it must pay for.

For AI, pricing “around the recognizable work” is what helps the startup prove its worth to the customer. When the fees revolve around, say, how many reports are processed, or tickets closed, or leads generated, this makes the product “economically valuable to both sides,” writes a16z partners Tugce Erten and Sarah Wang.

All of this means that AI has potentially ushered in a new era of enterprise experimentation. That opens doors to startups — enterprises are more willing to try their tech — but it also means an enterprise contract no longer secures long-term revenue. When or if enterprises will revert to their long-term buying habits remains to be seen.

Startup ARR is less secure than ever, new research shows

ServiceNow has made headlines by acquiring the Israeli startup Sweep in a transaction valued in the hundreds of millions of dollars. This move underscores the enterprise software company's ongoing commitment to enhancing its artificial intelligence and autonomous work initiatives. Official confirmations of the acquisition or its precise value have yet to be released by either party.

This acquisition arrives just a few weeks after ServiceNow secured the Israeli AI firm ai.work for tens of millions of dollars. It is part of a broader trend of significant acquisitions from Israeli companies, which includes renowned names such as cybersecurity firm Armis, analytics provider Pyramid Analytics, and AI observability platform Traceloop.

Sweep, founded in 2021 by Ido Gaver and Eran Kirshenboim, aims to create an "agentic workspace" tailored for go-to-market operations. Their notable funding achievements include a $22.5 million Series B round in May 2025, led by Insight Partners, alongside participation from Bessemer Venture Partners. The estimated size of the Sweep transaction is particularly noteworthy given the company’s total disclosed funding of $46 million.

The startup's innovative technology seamlessly integrates with major enterprise platforms like ServiceNow, Salesforce, and HubSpot. Sweep's software monitors metadata across these systems to pinpoint misalignments and bottlenecks, while also generating necessary documentation and offering contextual support for users.

Additionally, Sweep has been working on an "agentic layer" that aims to recommend or even enact changes rather than merely highlighting issues. This approach seeks to enhance the responsiveness of go-to-market teams, enabling AI to engage proactively with data inside enterprise applications, rather than just analyzing it.

Among Sweep's clientele are notable organizations such as Brex, LG Electronics, Mass General Brigham, NBC Sports, Exiger, and Wix. Gaver and Kirshenboim previously co-founded Flok, which was acquired by Wix.

This acquisition aligns with ServiceNow's broader strategy to fortify its AI agents and autonomous enterprise operations. Recent purchases have strategically targeted various segments of the technology stack. Earlier this year, ServiceNow acquired ai.work, a startup founded by ex-WalkMe executives Maor Ezer and Nir Nahum, which developed AI agents capable of managing internal processes across multiple business areas, including IT, operations, and finance.

ServiceNow's recent acquisition spree in Israel has significantly accelerated this year, highlighted by its major $7.75 billion acquisition of cybersecurity firm Armis, among others. The company has also recently acquired Pyramid Analytics for a substantial sum and Traceloop for an estimated $60 million to $80 million.

ServiceNow purchases Israeli AI startup Sweep in a deal valued at hundreds of millions.

A bright, sunlit corporate boardroom: two sharply dressed executives shake hands across a sleek glass table, city skyline visible through floor-to-ceiling windows. Behind them, a large wall display shows the ServiceNow logo prominently. On the table sits a small stand with the Israeli flag, hinting at the startup’s origin, while a subtle plaque reading “Sweep” rests nearby, symbolizing the acquisition deal.

ServiceNow acquires Israeli AI startup Sweep in deal estimated at hundreds of millions - calcalistech.com

- ServiceNow has acquired Israeli startup Sweep to enhance its AI and autonomous work capabilities.  
- The acquisition follows ServiceNow's recent purchase of ai.work and multiple Israeli tech acquisitions.  
- Sweep's technology aims to optimize enterprise systems, improving efficiency for go-to-market teams.  

ServiceNow has acquired Israeli startup Sweep in a deal estimated to be worth hundreds of millions of dollars, another major move by the enterprise software giant to expand its push into artificial intelligence and autonomous work. Neither company has officially announced the acquisition or disclosed its value.

The deal comes less than two months after ServiceNow acquired Israeli AI startup ai.work for tens of millions of dollars, and follows a much larger series of Israeli acquisitions that has included cybersecurity company Armis, analytics company Pyramid Analytics and AI observability startup Traceloop.

1 View gallery ServiceNow headquarters. ( Photo: David Paul Morris/Bloomberg )

"Sweep’s technology and expertise strengthen our AI-native development capabilities and advance agentic deployment for CRM. The impact for customers is direct: faster time-to-value as they scale agentic systems," ServiceNow told CTech in a written statement.

The estimated size of the Sweep transaction is notable given that the company has raised $46 million in disclosed funding. Founded in 2021 by Ido Gaver and Eran Kirshenboim, Sweep develops what it calls an “agentic workspace” for go-to-market operations. Its $22.5 million Series B round, announced in May 2025, was led by Insight Partners with participation from Bessemer Venture Partners.

Sweep’s technology works across enterprise platforms including ServiceNow, Salesforce and HubSpot. Its software monitors metadata across these systems, identifies misalignments and bottlenecks, generates documentation and provides contextual assistance to users.

The company has also been developing an “agentic layer” designed to recommend or implement changes rather than simply flag problems. The broader goal is to make the systems used by go-to-market teams more adaptive, allowing AI to act on information inside enterprise software rather than merely analyze it.

Sweep’s customers have included Brex, LG Electronics, Mass General Brigham, NBC Sports, Exiger and Wix.

Gaver and Kirshenboim previously launched Flok, a company that was acquired by Wix.

The acquisition comes as ServiceNow is building a broader strategy around AI agents and autonomous enterprise work, with recent purchases targeting different layers of the technology stack.

In July, ServiceNow acquired Israeli AI startup ai.work, founded by former WalkMe executives Maor Ezer and Nir Nahum. The company had developed AI agents capable of handling internal organizational processes across areas including IT, operations, legal, human resources, procurement, travel and finance.

ServiceNow’s Israeli acquisition spree has accelerated sharply this year. Its largest deal was the $7.75 billion purchase of Israeli cybersecurity company Armis, completed earlier this year. ServiceNow has also acquired Pyramid Analytics for several hundred million dollars and Traceloop for an estimated $60 million to $80 million.

ServiceNow acquires Israeli AI startup Sweep in deal estimated at hundreds of million

TechCrunch Disrupt 2026 is set to welcome back the Builders Stage, a vibrant platform for founders, startup leaders, and investors to engage in meaningful dialogues about the intricacies of building and scaling successful enterprises.

Attendees will hear insights from prominent figures in the startup and venture capital landscape, including Grant Lee, CEO and co-founder of Gamma; Leah Solivan, founder and general partner at Precedent.vc; and Robby Stein, VP of Product at Google, among others. These discussions will dive into real-world experiences, covering critical topics such as fundraising, talent acquisition, market strategy, artificial intelligence, and the operational tactics that drive startup success.

Join over 10,000 founders, investors, startup professionals, and tech innovators at the Moscone Center in San Francisco from October 13-15. Don’t miss your chance to secure tickets now and take advantage of early-bird pricing before the rates go up.

The Builders Stage is one of six specialized areas at Disrupt 2026, aimed at equipping founders with the tools necessary for growth. This includes guidance on securing funding, hiring skilled talent, creating marketing strategies, and transitioning from seed funding to Series A.

Each session is designed to offer immediate, actionable strategies, complemented by live Q&A opportunities with speakers. Register now for Disrupt 2026 and save up to $330 ahead of the ticket price hike.

Here’s a sneak peek at the Builders Stage agenda, with more details on speakers and topics to come as we approach the event.

**Builders Stage Agenda Highlights**

*Winning Strategies in an AI-Centric Market*  
With Shan Shan, Investment Manager at Baillie Gifford, and Yuri Sagalov, Managing Director at General Catalyst, this session will dissect essential growth elements like retention and revenue quality that persist even amidst the AI-driven hype.

*Understanding Competitive Landscape When OpenAI Affects Your Roadmap*  
Join Michel Tricot, CEO and Co-founder of Airbyte, Rob Toews from Radical Ventures, and Linda Tong, CEO of Webflow, as they discuss strategies to maintain defensibility in the face of fierce competition from AI giants.

*Scaling AI Startups: What Investors Seek*  
Jas Khaira from Blackstone N1 will share insights on what differentiates sustainable companies from fleeting successes, focusing on capital allocation as startups aim for scale.

*Attracting Top AI Talent*  
With Matt Birnbaum from Wylder.co and Ioana Hreninciuc from Runware, this session addresses the heightened challenges in hiring amidst rising employee expectations and evolving market conditions.

*Capitalizing on Pre-Seed Funding Without a Product*  
Puneet Agarwal from True Ventures will guide founders on how to secure initial funding based solely on vision and market potential.

*From MVP to Billion-User Success: Adapting Product Decisions*  
Robby Stein from Google discusses the complexities of product decision-making at scale, emphasizing the need to balance speed and reliability.

*Navigating AI in Team Dynamics*  
Led by Josh Reeves, co-founder of Gusto, this session investigates how startups can integrate AI into their operations while maintaining team cohesion.

*Rethinking Consumer Products for an AI-Driven World*  
Leaders from Reddit, Square, and Uber will explore how AI dynamics are reshaping product design and user interaction.

*Strategic Mergers and Acquisitions in Early Stages*  
Karl Alomar from M13 and Lindsey Mignano discuss building an M&A strategy from day one, adapting to shifting exit strategies.

*The Future of Series A Funding*  
This briefing will prepare founders for evolving standards in fundraising as investors become progressively discerning.

*Accelerating Revenue Growth in 90 Days*  
Industry experts share strategies on how AI is shortening the time frame for achieving significant revenue milestones.

*Innovating Across Multiple Models in AI*  
A panel of founders will discuss the need for agility in product development within a rapidly changing technological landscape.

*Exploring the Potential of AI Beyond Current Models*  
Shay Grinfeld of Greenfield Partners will lead a discussion on the future capabilities of AI, featuring the unveiling of the 2026 AI Disruptors 60—highlighting companies pushing the technological boundaries.

*Understanding True Product-Market Fit*  
Rajeev Dham from Sapphire Ventures provides critical insights on recognizing genuine traction amidst the noise of market excitement.

*Gaining Your First 1,000 Customers on a Shoestring*  
Founders Lee, Solivan, and Wallen will reveal how creative strategies and grassroots efforts drive initial customer acquisition.

*The Psychological Realities of Being a Founder*  
A discussion featuring Nell Daly and David H. Rosmarin will delve into the often-overlooked mental and emotional challenges of navigating high-growth environments.

*Scaling Beyond a Single Hit Product*  
Founders Kaliszan and Jacobson dissect the frameworks for creating a sustainable, multi-product innovation strategy.

*Recruitment Strategies in a Competitive Talent Market*  
Matt Birnbaum and Atli Thorkelsson address the shifting dynamics of hiring and the evolving expectations of today’s workforce.

*Harnessing Viral Growth*  
Zach Yadegari will share tactics for leveraging initial viral success and converting it into lasting engagement.

*Investor Insights: The Key to Securing Funding*  
In an interactive Q&A, investors will shed light on what characteristics make a startup attractive for investment.

Get ready to engage in essential conversations and forge valuable connections at Disrupt 2026. If you're eager to enhance your understanding and capabilities in this evolving startup landscape, secure your pass today!

Disrupt 2026 agenda unveiled by builders

A sunlit, modern conference hall where a presenter at a sleek podium gestures toward a giant screen reading “Builders Stage – Agenda Revealed, Disrupt 2026,” framed by blueprint-style graphics; on one side of the stage, a table displays miniature hardware prototypes and circuit boards; rows of adult attendees in business-casual tech attire take notes on laptops and tablets under warm natural light, with a branded “Disrupt 2026” banner hanging overhead.

Builders Stage agenda revealed for Disrupt 2026 - TechCrunch

- The Builders Stage at TechCrunch Disrupt 2026 focuses on practical strategies for startup growth.  
- Over 10,000 attendees, including founders and investors, will gather in San Francisco.  
- Expert sessions will cover fundraising, hiring, AI strategies, and adapting to market demands.  

The Builders Stage is returning to TechCrunch Disrupt 2026, bringing together founders, startup operators, and investors for practical conversations on what it takes to build and scale successful companies.

Hear from startup and venture leaders shaping the tech ecosystem, including Grant Lee, CEO and co-founder of Gamma; Leah Solivan, founder and general partner at Precedent.vc; Robby Stein, VP of Product at Google; and more. Through candid conversations and real-world case studies, speakers will share actionable insights on fundraising, hiring, go-to-market strategy, AI, and the operational decisions that fuel startup growth.

Join more than 10,000 founders, investors, startup operators, and technology leaders at Moscone Center in San Francisco on October 13-15. Register today and save before our next ticket price increase.

Image Credits:TechCrunch

Built for founders who are ready to scale

Building a startup is one thing. Building a company that can scale is another challenge entirely. The Builders Stage is one of six industry-focused stages at Disrupt 2026, dedicated to helping founders navigate the challenges of growth, from raising capital and hiring top talent to building go-to-market engines and preparing for the jump from seed to Series A.

Every session delivers practical strategies you can put to work immediately, plus opportunities to engage directly with speakers during live Q&A. Secure your pass to Disrupt 2026 today and save up to $330 before rates increase.

Without further ado, here’s your first look at the Builders Stage agenda, with more speakers and sessions to be announced as we get closer to the event.

Builders Stage agenda

How to Win When You’re Not Building AI

With Shan Shan, Investment Manager, Baillie Gifford; and Yuri Sagalov, Managing Director at General Catalyst

AI may dominate the world of venture, but many enduring companies won’t be those that sell AI models or agents. This session is for founders competing for attention in an AI-obsessed market. Panelists break down what actually matters now: efficient growth, retention, revenue quality, and disciplined execution, and why fundamentals, not hype, still build breakout businesses.

What Happens When OpenAI Ships Your Roadmap

With Michel Tricot, CEO and Co-founder, Airbyte; Rob Toews, Partner, Radical Ventures; and Linda Tong, CEO, Webflow

Nearly all AI founders have the same worry these days: What if OpenAI or Anthropic launches a product that competes with mine? Even strong products are at risk of becoming features of the larger players. This session explores where defensibility exists and what founders can do if they do face competition from rapidly evolving AI giants.

Building the Next Generation of AI Giants

With Jas Khaira, Global Head, Blackstone N1

AI startups are scaling faster, and demanding more capital, than any generation before them. Jas Khaira, Global Head of Blackstone N1, shares what separates enduring companies from early momentum, how founders should think about capital as they scale, and what Blackstone looks for when backing the next generation of category-defining businesses.

Competing for AI Talent: Pay, Equity, and Retention

With Matt Birnbaum, Founder, Wylder.co, Ioana Hreninciuc, Runware, Atli Thorkelsson, VP, Talent Network, Redpoint Ventures

The growth of AI startups has made hiring and retention more difficult for every tech company. From competing for AI talent to navigating secondary sales, founders are rethinking the human infrastructure of their startups. As incentives and employee expectations rapidly evolve, this session explores how companies are adapting compensation, culture, and team-building strategies to attract and retain top talent in a fundamentally changed market.

Winning Pre-Seed Without a Product

With Puneet Agarwal, Managing Partner, True Ventures; Austin Clements, Managing Partner, Slauson and Co; and Sandhya Venkatachalam, Founder and Managing Partner, Axiom Partners

Founders are increasingly expected to compete for capital before they even have a product. At the pre-seed stage, investors are betting on story, conviction, and founder-market fit. This session breaks down how to build credibility before revenue exists so investors will cut that first check.

From MVP to Billions of Users: How Product Decisions Must Change at Scale

With Robby Stein, VP, Product, Google

The instincts that win when building your first minimum viable product can break you at a billion-user scale. In this fireside, Robby Stein shares how product decision-making changes when every update impacts billions of users. Hear how teams balance speed with trust and innovation with reliability at one of the world’s largest product organizations.

Hiring When AI Is a Co-Founder

With Josh Reeves, CEO and Co-founder, Gusto; more speakers to be announced

Early-stage companies are no longer just building with AI; they’re hiring it. As AI agents take on engineering, support, and operations, the definition of an early team is being rewritten. This session explores how founders decide what humans should own versus what gets delegated to AI, and how high-growth startups are building hybrid teams without losing speed, accountability, or culture.

Rebuilding Consumer Products for the AI Era

With Maria Angelidou-Smith, CPO, Reddit

AI isn’t just adding features, it’s forcing product teams to rethink how people search, discover, communicate, travel, and make decisions. Leaders from Reddit, Square and Uber discuss how they’re redesigning products used by millions, what users actually want from AI, and where product leaders should resist the temptation to automate everything.

M&A Is Now an Early-Stage Strategy

With Karl Alomar, Managing Partner, M13 and Lindsey Mignano, Founder, Mignano Law Group

The smartest founders today aren’t just building for IPOs; they’re also building with possible acquisitions in mind from day one. As exits shift and capital tightens, understanding M&A early has become a competitive advantage. This session breaks down how founders can create the possibility of such an option through product strategy and partnerships. It delves into how big-dollar startup outcomes actually happen, even for small companies.

The Series A in 2027

Jahanvi Sardana, Partner, Index Ventures; Shailendra Singh, Managing Director, Peak XV; and Janelle Teng Wade, Partner, Bessemer Venture Partners

Series A is getting harder, with VCs growing more demanding. For founders planning to raise in the next one to two years, this session breaks down what “fundable” will actually mean in 2027. Hear how top investors are redefining the metrics, teams, and traction that matter now, what outdated fundraising playbooks no longer work, and how companies can separate from the pack in the next funding cycle.

The 90-Day GTM: Why $0–$10M ARR Is the New Baseline (and How to Actually Get There)

With Ryan Meadows, Chief Revenue Officer, Lovable; and Tomasz Tunguz, General Partner and Founder, Theory Ventures; Ben Broca, Founder, Polsia

The definition of traction has changed. What once took years is now expected in months, and $0 to $10 million ARR is increasingly becoming the new early-stage baseline. This session breaks down how AI-enabled execution, faster distribution, and shifting investor expectations are compressing GTM timelines, and the tactical levers founders need in the first 90 days to accelerate revenue and stand out fast.

The Real Tokenmaxxing: How the Best AI Companies Navigate a Multi-Model World

With Mo Jomaa, Partner, Capital G; and Zuzanna Stamirowska, CEO and Co-founder, Pathway; more speakers to be announced

The frontier is moving faster than any single model can keep up with, and the teams building the most successful AI products are increasingly orchestrating across many models rather than betting on just one. This panel brings together founders and operators at the center of that shift to discuss how they evaluate new models, manage cost and reliability at scale, and architect products that can evolve as quickly as the underlying technology.

Revealing AI Disruptors 60: What Can AI Do Next?

With Shay Grinfield, Greenfield Partners

The AI conversation is shifting from what models can say to what they can actually do. Agents are navigating the open web and completing work, AI systems are taking on increasingly ambitious research, intelligent machines are beginning to operate beyond the screen, and a new infrastructure layer is emerging to make all of this possible at scale.

Greenfield Partners’ Shay Grinfeld sits down with founders building across these emerging areas to separate what’s real today from what’s coming next, and explore where the biggest new opportunities are taking shape. The conversation will culminate in the reveal of Greenfield Partners’ 2026 AI Disruptors 60, spotlighting the companies Greenfield and TechCrunch believe are pushing AI into new territory.

PMF Red Flags: How to Tell If You Really Have It

With Rajeev Dham, Managing Director, Sapphire Ventures; and Rahul Vohra, Founder and Head of Superhuman Mail; more speakers to be announced

In an AI hype cycle, product-market fit signals are easier to fake and harder to trust. Founders are mistaking early excitement, usage spikes, and pilot wins for durable traction. This session breaks down what false PMF actually looks like, how investors and operators separate real retention from hype-driven adoption, and the signals that indicate whether a company has true pull or just temporary momentum.

The Zero-to-1K Playbook: How to Get Your First 1,000 Customers Without a Marketing Budget

With Grant Lee, CEO and Co-founder, Gamma; Leah Solivan, Founder and General Partner, Precedent.vc; and Elia Wallen, Founder and CEO, Engine

Early customer acquisition is not about marketing spend; it’s about founder-led distribution and relentless execution. Most startups at zero to one do not have budget, brand, or scale, only urgency and creativity. This session breaks down how founders are landing their first customers through community building, product-led growth, founder-led sales, strategic outbound, and word-of-mouth momentum.

Yes, It’s Hard to Be a Founder: An Honest Conversation

With Nell Daly, Co-founder and Managing Partner, Revenge Capital; David H. Rosmarin, Associate Professor, Harvard Medical School; and Jack Withinshaw, Co-founder and Chief Commercial Officer, Airspeeder

Company building is as psychologically demanding as it is strategic, and most founder narratives understate that reality. In this candid conversation, founders and mental performance experts unpack the hidden costs of high-growth environments, from burnout and decision fatigue to the identity strain of sustained pressure, and share the systems, habits, and mental frameworks that help leaders endure and perform at a high level.

So You’ve Got a Hit Product. How Does Your Company Do It Again?

With Filip Kaliszan, CEO and Co-founder, Verkada; and Aaron Jacobson, Partner, New Enterprise Associates; Maddi Holman, General Partner, Daring Ventures

Most startups stall out because they build a single great product instead of a repeatable multi-product engine. Join a venture capitalist and two founders as they reveal the precise operational playbook for capital allocation, systemizing internal innovation, and engineering a compounding “Second Act” before the core product’s growth curve flattens.

Hiring, Compensation and Culture in the Most Competitive Market Ever

With Matt Birnbaum, Founder, Wylder.co; and Atli Thorkelsson, VP, Talent Network, Redpoint Ventures; more speakers to be announced

No question about it, the growth of AI startups has made hiring and retention for all tech companies more difficult. From competing for AI talent to secondary sales, founders are rethinking the human infrastructure of their startups. As hiring, incentives, and employee expectations rapidly evolve, this session explores how companies are adapting compensation, culture, and team-building strategies to attract and retain top talent in a fundamentally changed startup environment.

How to Create Viral Growth and Capitalize on It

With Zach Yadegari, Founder, Cal AI

Startups can go from zero to viral overnight, but sustaining that momentum is a completely different challenge. In this fireside, Zach Yadegari shares how Cal AI navigated rapid growth, product pressure, and the realities of building in a distribution-driven market. Hear the lessons behind turning breakout attention into durable retention and long-term company building.

The High-Conviction Filter: What We Learned From the Battlefield

With Alexa von Tobel, Inspired Capital; and Chi-Hua Chien, Co-founder and Managing Partner, Goodwater Capital; more speakers to be announced

What separates the breakout companies from the rest at TechCrunch Disrupt 2026? In this candid debrief, Startup Battlefield judges unpack the trends and founder qualities that stood out in real time, from shifting investor expectations to the narratives that resonated most this year. The conversation will also explore how startup storytelling is evolving and what happens after the spotlight, including the realities of maintaining momentum and surviving the critical 12 months after a major launch, funding round, or Startup Battlefield appearance.

Ask the Investors

With Stacy Brown-Philpot, Founder & Managing Partner at Cherryrock Capital; Chi-Hua Chien, Co-founder & Managing Partner, Goodwater Capital; Dayna Grayson, Construct Capital; Carter Reum, Co-founder and Managing Partner, M13; Alexa Von Tobel, Inspired Capital

What makes an investor say yes? In this audience-led Q&A, the Startup Battlefield finals judges take your toughest questions on what separates a fundable startup from the rest: team, traction, market opportunity, pitch delivery, red flags, and more. Come ready to ask and get candid answers straight from the investors making the decisions.

Join the conversations and make the connections at Disrupt

If you’re ready to build smarter, scale faster, and learn from the leaders shaping the future of startups, secure your pass to TechCrunch Disrupt 2026 today.

Builders Stage agenda revealed for Disrupt 2026

Adobe has successfully added to its portfolio by acquiring Rilo, a marketing intelligence startup based in India, through a deal that encompasses both licensing and team acquisition, as confirmed by TechCrunch and the company itself. This marks Adobe's second acquisition from India, following its purchase of the video platform Rephrase.ai earlier in 2023. The specific financial terms of the deal remain undisclosed.

While Adobe has verified the acquisition, the company has abstained from providing further comments.

The integration of Rilo brings with it a talented team and cutting-edge technology that focuses on the automation of marketing workflows. As businesses increasingly turn to AI to enhance the creation, deployment, and monitoring of marketing campaigns, Rilo's tools can help streamline processes, extract action items from meetings or calls, and elevate brand presence on platforms like ChatGPT, Gemini, and Claude. This technology is poised to enhance Adobe's existing offerings, particularly for its enterprise clientele.

Rilo was founded in 2025 by IIT alumni Georgi Boby and Dhruv Jaglan and had managed to secure $1 million from notable investors such as Peak XV, DeVC, and Day Zero Ventures, achieving a valuation of $10 million. According to sources, investors will see returns from this transaction, and Adobe plans to assimilate some of Rilo's intellectual property along with a six-member team. Jaglan highlighted on LinkedIn that over 10,000 users had tested their product.

The startup specialized in enabling go-to-market teams to develop tailored workflows that included competitor analysis, content repurposing and distribution, as well as sales call evaluations. Rilo's offerings were comparable to established tools like Claude Cowork and ChatGPT Work, allowing for a high degree of customization.

In light of the acquisition, Rilo will cease operations and its services will no longer be available to existing customers.

Dhruv Jaglan and Georgi Boby, co-founders of Rilo, received positive remarks from Rahul Gupta, managing partner at Day Zero Ventures, who expressed enthusiasm over the speed of the acquisition and recognized the potential of Rilo's innovative workflow builder to enhance productivity at a major company like Adobe.

Additionally, Adobe made headlines last year with its notable acquisition of SEO firm Semrush for $1.9 billion, expanding its reach in the marketing technology domain.

DeVC’s Rahul Mathur suggested that Rilo’s capabilities could seamlessly integrate into Adobe’s customer experience (CX) and marketing ecosystem, simplifying complex workflows and offering users greater visibility into their activities on Adobe's platform.

In the competitive landscape, other players like Canva are also enhancing their marketing offerings through acquisitions and new product launches. Meanwhile, tech giants such as Amazon, Google, and Meta are developing their own AI-driven marketing infrastructures. The article has been revised to include insights from the co-founders regarding user engagement with Rilo’s tool.

Adobe purchases Indian market analysis company Rilo.

A bright, sunlit modern office lobby: on one glass wall, a bold red Adobe logo; on the adjacent wall, a sleek “Rilo” sign in orange and teal inspired by Indian textiles. Warm natural light streams through a skylight onto a polished marble floor. Beside the entrance, a single Indian flag flutters gently. In the background, a large digital dashboard displays ascending market intelligence charts, symbolizing growth and integration.

Adobe acquires Indian market intelligence startup Rilo - TechCrunch

- Adobe acquires Indian startup Rilo to enhance marketing automation capabilities and technology.  
- Rilo, founded in 2025, raised $1 million prior to its acquisition by Adobe.  
- Post-acquisition, Rilo will shut down and cease operations for existing customers.  

Adobe has acquired India-based marketing intelligence startup Rilo in a deal involving licensing and team acquisition, TechCrunch learned and the company confirmed. This is Adobe’s second acquisition from India after it bought video platform Rephrase.ai in 2023. The companies didn’t disclose the deal’s terms.

Beyond confirming the deal, Adobe declined to comment.

The acquisition gives Adobe a small team and technology focused on automating marketing workflows, which have been changing as companies use AI to build tools to automate the creation, deployment, and tracking of campaigns, get action items from meetings or calls to complete tasks, and increase brand visibility on platforms like ChatGPT, Gemini, and Claude. Rilo’s technology could bolster Adobe’s existing products as the company targets its larger customers.

Founded by IIT batchmates Georgi Boby and Dhruv Jaglan in 2025, Rilo raised $1 million from investors including Peak XV, DeVC, and Day Zero Ventures at a $10 million valuation. A source told TechCrunch that investors will get an exit from this deal, and Adobe will integrate some of Rilo’s IP along with the six-member team. Jaglan mentioned on LinkedIn that more than 10,000 people had tried out the tool.

The company worked on letting go-to-market teams create custom workflows, including competitor intelligence, content repurposing and distribution, and sales call analysis. It also allowed teams to set up custom workflows comparable to tools like Claude Cowork and ChatGPT Work.

Post-acquisition, Rilo will shut down and won’t be available to its customers.

Rilo co-founders Dhruv Jaglan and Georgi Boby Image Credits:Rilo

“We’re very excited that Rilo has been acquired by Adobe in such a short span of time,” Rahul Gupta, managing partner, Day Zero Ventures told TechCrunch over email. “Their workflow builder product was way ahead of the curve and shall be extremely valuable to a giant like Adobe in enhancing customer experience and productivity.”

Adobe made a marquee marketing acquisition last year by buying SEO optimization company Semrush for $1.9 billion.

DeVC’s Rahul Mathur told TechCrunch that Rilo could fit into Adobe’s CX and marketing suite to handle complex workflows and give customers visibility into actions they take on the creative company’s platform.

Rivals like Canva have also bolstered their marketing portfolio with acquisitions and new launches. Meanwhile, Amazon, Google, and Meta have built their own AI-powered marketing rails.

The story has been updated with co-founders’ post mentioning the stat.

Adobe acquires Indian market intelligence startup Rilo

Lyte, a cutting-edge startup focused on robotics and artificial intelligence, has successfully secured $165 million in funding, boosting its valuation to $1.6 billion—an impressive increase that has nearly tripled its worth in less than a year. This latest investment elevates the company's total funding to $272 million.

Based in Mountain View, California, Lyte finds itself in the company of a rising number of startups attracting major investments aimed at creating the hardware and infrastructure necessary to integrate AI into the physical realm.

The company is backed by a combination of experienced semiconductor entrepreneurs and engineers. Avigdor Willenz, one of Israel's notable figures in the semiconductor industry, serves as the founding investor and chairman. The team also includes engineers who played pivotal roles in developing the depth-sensing technologies underpinning Apple's Face ID.

Maverick Silicon co-led this funding round, which also saw participation from Fidelity Management & Research, Atreides Management, Key1 Capital, and Ora Global. Exor Ventures, an early supporter, continues to invest in Lyte.

This new funding comes just eight months after Lyte announced its presence to the public on January 5 with an initial $107 million in funding. Since that announcement, the startup has more than doubled its investments and surpassed the $1 billion valuation mark.

Willenz’s partnership reinforces Lyte's connection to a legacy of influential Israeli semiconductor firms that have become significant players in technology innovation. He established Galileo Technologies, which specialized in networking chips and went public on Nasdaq before being acquired by Marvell in a deal worth approximately $2.7 billion. Willenz was also an early investor in Annapurna Labs, which created processors for Amazon’s cloud services, and he co-founded Habana Labs, an Israeli company specializing in AI processors, which Intel acquired in 2019 for roughly $2 billion.

Lyte's strategic focus is on a new layer of technology poised to grow in relevance as artificial intelligence expands beyond data centers. "Lyte is building at the right layer, at the right moment,” Willenz remarked upon the company’s debut. “I’ve witnessed how fundamental technologies can revolutionize entire industries. What is particularly noteworthy here is the depth of expertise in the team and their commitment to addressing perception as a system, where substantial value is generated."

The founders of Lyte each bring significant experience in perception technology to the table. CEO Alexander Shpunt co-founded PrimeSense, the Israeli company behind the technology that powered Microsoft's Kinect. Apple acquired PrimeSense in 2013 for $350 million, after which its technology was integrated into Apple’s depth-sensing platform. Following this, Shpunt served at Apple as a Distinguished Engineer, focusing on perception systems utilized across various products.

CTO Arman Hajati's journey diverged from Shpunt’s but is equally distinguished. Hailing from Iran and educated at the University of Tehran, he honed his engineering skills in the U.S. and eventually became a senior engineering manager at Apple, specializing in integrated sensing technologies that inform Lyte’s current methodology.

The third key founder, Yuval Gerson, is another PrimeSense veteran who transitioned to Apple as a MEMS system architect before taking on his role at Lyte as an engineering fellow and vice president.

While Lyte is not developing a physical robot, its aim is to create foundational technology that enables robots and autonomous machinery to better perceive and interact with their environments. Lyte’s premier offering, LyteVision, merges 4D sensing, RGB imaging, and motion awareness into a comprehensive perception platform. The company is also focused on crafting custom silicon and software to seamlessly integrate these elements.

Lyte is tackling a critical challenge as robotics continue to evolve. Although AI models have made strides in processing language, images, and other digital data, autonomous systems must also navigate and interpret ever-changing physical surroundings. Typically, robotics companies gather various sensors and components from multiple suppliers but often face the daunting task of integrating and calibrating these elements while developing software to process the data effectively.

Lyte secures $165 million funding at a $1.6 billion valuation as investors flock to physical AI.

A bright, sunlit modern lab: in the center, a sleek silver humanoid robot stands on a glass pedestal as golden dollar coins rain down around its limbs. Behind it, a large Lyte logo is etched into a frosted glass wall. Around the pedestal, a half-circle of sharply dressed investors watches with raised glasses, their reflections stretching on the polished white floor.

Lyte raises $165 million at $1.6 billion valuation as investors pile into physical AI - calcalistech.com

- Lyte raised $165 million, tripling its valuation to $1.6 billion in under a year.  
- The startup focuses on improving perception systems for robotics and autonomous machines.  
- Founders include veterans from PrimeSense and Apple, enhancing technology for physical AI applications.  

Lyte, a robotics and artificial intelligence startup founded by veterans of Apple and Israeli 3D-sensing company PrimeSense, has raised $165 million at a valuation of $1.6 billion, roughly tripling its value in less than a year and bringing its total funding to $272 million.

The round puts the Mountain View, California-based company among a growing group of startups attracting substantial capital for the hardware and infrastructure needed to bring artificial intelligence into the physical world.

1 View gallery Avigdor Willenz. ( Photo: Eyal Toueg )

It also brings together two generations of semiconductor entrepreneurs and engineers. Lyte's founding investor and chairman is Avigdor Willenz, one of Israel's most successful semiconductor entrepreneurs, while the company's founding team includes engineers who helped develop the depth-sensing technologies behind Apple's Face ID.

The latest round was co-led by Maverick Silicon, with participation from Fidelity Management & Research, Atreides Management, Key1 Capital and Ora Global. Exor Ventures, which participated in earlier financing, is also among Lyte's backers.

The new funding comes just eight months after Lyte emerged from stealth on January 5 with $107 million in aggregate funding. Since then, the company has more than doubled the capital it has raised and crossed the $1 billion valuation threshold.

Willenz's involvement gives Lyte a connection to a long history of Israeli semiconductor companies that went on to become important technology platforms.

Willenz founded Galileo Technologies, which developed networking chips and went public on Nasdaq before being acquired by Marvell in 2000 in a transaction valued at about $2.7 billion.

He later became an early investor in Annapurna Labs, a chip company that developed processors for Amazon's cloud infrastructure and was acquired by Amazon in 2015. He was also a founder and early investor in Habana Labs, an Israeli developer of AI processors that Intel acquired in 2019 for about $2 billion.

Willenz is now betting on another layer of technology that could become increasingly important as artificial intelligence moves beyond data centers.

"Lyte is building at the right layer, at the right moment," Willenz said when the company emerged from stealth. "I've seen how foundational technologies unlock entire industries. What stands out here is the depth of the team and the discipline to solve perception as a system, where lasting value is created."

Lyte's founders bring their own history in perception technology.

CEO Alexander Shpunt co-founded PrimeSense, the Israeli 3D-sensing company whose technology powered Microsoft's Kinect. Apple acquired PrimeSense in 2013 for $350 million, and the technology subsequently became part of Apple's depth-sensing platform.

Shpunt later worked at Apple as a Distinguished Engineer, where he focused on perception systems used across the company's products.

The company's CTO, Arman Hajati, followed a different path. Born in Iran and educated at the University of Tehran, he built his engineering career in the United States and eventually became a lead system architect and senior engineering manager at Apple, working on the tightly integrated sensing technologies that now inform Lyte's approach.

The third founder, Yuval Gerson, is another veteran of PrimeSense. He later worked at Apple as a MEMS system architect before joining Lyte as an engineering fellow and vice president.

Lyte is not building a robot. Its ambition is to supply some of the underlying technology that allows robots and other autonomous machines to understand their surroundings.

Its flagship product, LyteVision, combines 4D sensing, RGB imaging and motion awareness into an integrated perception platform. The company is also developing custom silicon and software designed to bring those components together.

The problem Lyte is targeting is one that has become more important as robotics advances. While AI models have made rapid progress in understanding language, images and other digital information, autonomous machines must also interpret constantly changing physical environments.

Robotics companies typically combine different sensors and components from multiple suppliers, then spend significant engineering resources integrating and calibrating them and developing software capable of combining the resulting data.

Lyte raises $165 million at $1.6 billion valuation as investors pile into physical AI

The fundraising momentum at Israeli startup Wonderful shows no signs of diminishing. This innovative company has created an operating system tailored for enterprise AI and has successfully secured around $550 million in a Series C funding round, achieving a remarkable valuation of roughly $5 billion. This latest influx of capital comprises the $550 million raised as well as an additional $170 million generated through a secondary transaction, during which shares were sold by early investors and employees who had previously supported the company.

Originally, Wonderful launched its services in various countries, including Israel, catering to the development of AI agents for different organizations. Over time, the company’s technology has expanded, evolving from merely voice and operational agents to encompass a range of multidisciplinary agents and software development systems.

The sheer magnitude of this funding round is noteworthy, as is the rapid rise in the company’s valuation. Just six months prior, Wonderful had raised $150 million with a valuation of $2 billion. Since its inception in early 2025, Wonderful has accumulated over $800 million in funding.

Insight Partners spearheaded this latest funding round, joined by notable participants such as Salesforce and existing investors like Index Ventures, IVP, Vine Ventures, 9Yards, and Bessemer Venture Partners.

Currently, Wonderful boasts an estimated annual revenue run rate of $70 million, and projections indicate that it could exceed $100 million by year-end.

The newly acquired funds will be directed toward global expansion efforts and further enhancement of its enterprise AI operating system, all aimed at addressing the increasing demand from larger organizations.

Since its previous round of funding in March 2026, Wonderful has made significant strides, entering over 35 global markets and expanding its workforce to about 650 employees, with nearly half based in Israel. The company has also enriched its platform's capabilities, which are designed to automate comprehensive business processes through AI.

Founded in early 2025 by Bar Winkler, the CEO, and Roey Lalazar, the CTO, Wonderful has a strong foundation. Winkler is recognized for his earlier venture, Approve.com, an automated payment management platform acquired by Tipalti in 2021, while Lalazar previously launched Kaps, an AI-driven localization platform.

Wonderful positions its product as a comprehensive operating system for enterprise AI, synthesizing the necessary tools, capabilities, and controls for deploying and managing AI throughout organizations.

As part of its growth strategy, Wonderful intends to triple the size of its development and implementation center in Israel over the next year, aimed at bolstering local operations and advancing the company's platform development.

The operating system provided by Wonderful offers a universal management layer for AI applications within an organization. Constructed as an open platform, it does not rely on a single AI model and is built to integrate seamlessly with clients' existing technological environments.

A major contributor to Wonderful’s swift expansion is its unique deployment model. In addition to supplying the software platform, the company employs forward-deployed engineers (FDEs) to facilitate the implementation of AI applications for clients, aiding them in scaling these technologies across their operations.

This approach aligns with a wider trend in enterprise AI, as companies evolve from merely testing isolated AI applications to seeking comprehensive methods for deploying this technology across various sectors of their operations.

Wonderful secures $550 million at a $5 billion valuation merely six months following a $2 billion round.

A sunlit modern startup loft with floor-to-ceiling windows, where two executives clasp hands over a sleek glass table. Behind them, a large digital screen shows “$550M Raised” and a soaring line chart hitting “$5B Valuation.” The Wonderful logo hangs prominently on the wall, bathed in warm morning light, while stacks of funding documents and celebratory coffee cups rest on the table.

Wonderful raises $550 million at $5 billion valuation just six months after $2 billion round - calcalistech.com

- Israeli startup Wonderful raised $550 million, achieving a $5 billion valuation in Series C.  
- Founded in early 2025, Wonderful has raised over $800 million in total funding.  
- The company plans to triple its development center in Israel to support global expansion.  

The fundraising frenzy at Israeli startup Wonderful shows no sign of slowing. The company, which has developed an operating system for enterprise AI, has raised approximately $550 million in a Series C round at a valuation of about $5 billion. In addition to the $550 million that went into Wonderful's coffers, investors put another $170 million into a secondary transaction, purchasing shares from employees and angel investors who backed the company in its early days.

Wonderful initially launched in several countries, including Israel, with a product for developing AI agents for organizations. Its technology has since evolved from voice and operational agents to multidisciplinary agents and software development systems.

1 View gallery Wonderful founders. ( Photo: Daniel Jackont )

The size of the round is striking, but so is the speed at which Wonderful’s valuation has increased. Just six months ago, the company raised $150 million at a $2 billion valuation. Since its founding in early 2025, Wonderful has raised more than $800 million in total.

The latest round was led by Insight Partners and included participation from Salesforce and existing investors Index Ventures, IVP, Vine Ventures, 9Yards and Bessemer Venture Partners.

Wonderful has reached an estimated annual revenue run rate of $70 million and is expected to surpass $100 million by the end of the year.

The new capital will be used to expand Wonderful’s operations worldwide and continue developing its operating system for enterprise AI, as the company seeks to meet growing demand from large organizations.

Since its previous funding round in March 2026, Wonderful has expanded into more than 35 markets worldwide and now employs approximately 650 people, about half of them in Israel. At the same time, the company has expanded the capabilities of its platform, which is designed to automate entire end-to-end business processes using AI.

Wonderful was founded in early 2025 by Bar Winkler, who serves as CEO, and Roey Lalazar, its CTO. Winkler previously founded Approve.com, a platform for automated payment management for businesses that was sold to Tipalti in 2021. Lalazar previously founded Kaps, an artificial intelligence-based localization platform.

The company now describes its product as a complete operating system for enterprise AI, bringing together the tools, capabilities and controls required to deploy and manage AI across organizations.

As part of its expansion, Wonderful plans to triple the size of its development and implementation center in Israel over the coming year. The expansion is intended to support the growth of its local operations while continuing development of the company's platform.

Wonderful’s operating system provides a common management layer for AI applications across an organization. It is built as an open platform that does not depend on a single AI model and is designed to work with customers’ existing technological infrastructure.

One factor behind the company’s rapid growth is its deployment model. In addition to providing the software platform, Wonderful uses forward-deployed engineers, or FDEs, to implement AI applications for customers and help them scale those applications across their organizations.

The approach reflects a broader shift in enterprise AI, as companies move beyond testing individual AI applications and begin looking for ways to deploy the technology across multiple parts of their operations.

Wonderful raises $550 million at $5 billion valuation just six months after $2 billio

If you find that your gaming setup is mostly idle these days, two emerging companies are stepping in with an intriguing opportunity to monetize that downtime. Far Labs, based in Abu Dhabi, and Evolving Edge from Austin, are developing platforms designed to offload artificial intelligence (AI) inference tasks to underutilized consumer hardware, as reported by IEEE Spectrum.

Far Labs is gearing up to introduce its Far AI platform soon, boasting a low latency of 100 milliseconds or less, while Evolving Edge is currently in an open beta phase. "Think of it as the Uber or Airbnb for AI inference tasks," stated Ilman Shazhaev, the CEO and founder of Far Labs. Both startups are focusing on smaller, open-source AI models, rather than the more resource-intensive frontier models. They are entering a competitive arena that includes established players like Salad, a Utah-based platform that actively connects over 60,000 consumer GPUs daily.

The technology employed by Far Labs involves a specialized scheduler that breaks down AI models into manageable sections, which are then processed across multiple machines. An orchestrator and load balancer work together to reassemble these sections into a complete response. Meanwhile, Evolving Edge utilizes Ray, an open-source framework commonly found in traditional data centers, to facilitate job distribution.

Naturally, allowing external workloads onto personal systems can pose risks, such as exposure to malicious software or unauthorized access to local data. To mitigate these concerns, both companies implement robust isolation techniques. Inference workloads operate within a sandboxed environment, supported by encrypted communications and stringent limitations on GPU, CPU, memory, storage, and network access. Users of Evolving Edge are assured that their machines remain secure, particularly since the company has made its node software open-source, enabling hosts to audit the processes running on their devices.

Salad offers consumer GPU processing services at rates as low as $0.02 per hour, with GPU owners receiving only a fraction after the platform takes its fee. A review of Salad in 2021 revealed that it had generated around $3.6 million from users’ hardware, while dishing out approximately $500,000 in rewards. This resulted in a return of about 14 cents for every dollar contributed by users. However, electricity costs can erode potential profits: running an RTX 4090 at full load can consume 350W to 450W, translating to roughly $40 to $50 monthly at $0.15 per kWh, meaning that if your rig earns less than these expenses, it might just be losing money. Yet, details on payouts for the new platforms remain unspecified in the IEEE Spectrum report.

Both Shazhaev and John Federico, CEO of Evolving Edge, emphasize the resilience of distributed networks, which can withstand failures that typically paralyze centralized cloud services. Federico referenced a significant AWS outage that left smart devices unresponsive and stated that even if his network lost 100 out of 250,000 nodes, the system would continue to function normally.

Despite the advantages, distributed AI computing still faces skepticism. A research preprint from June highlighted concerns, pointing to Pearl, a blockchain initiative claiming to convert cryptocurrency mining into AI processing, which was found to operate the equivalent of 320,000 RTX 3090 GPUs on tasks yielding no significant AI outcomes. In contrast, Far Labs and Evolving Edge focus on real AI inference jobs rather than token incentives, positioning themselves as a more credible option, though their claims regarding costs and latency need validation as they scale up their operations.

Startups aim to lease your unused gaming PC for AI tasks — Proposing an 'Airbnb for AI inference,' but profitability is still uncertain.

A sunlit urban loft with warm morning light spilling across a sleek gaming PC tower perched on a small pedestal, a handcrafted “For Rent” tag dangling like an Airbnb keychain. At a nearby desk, a driven entrepreneur studies AI inference graphs on a laptop, streams of glowing orange data arcs flowing between the laptop screen and the GPU rig. Behind them, a chalkboard sketch shows a house icon morphing into a graphics card labeled “Airbnb for AI.”

Startups want to rent your idle gaming PC for AI tasks — Startups pitch an 'Airbnb for AI inference,' but profitability remains unproven - Tom's Hardware

- Startups Far Labs and Evolving Edge are creating marketplaces for AI inference on idle PCs.  
- Both platforms emphasize security with sandboxed workloads and encrypted communication for user safety.  
- Distributed networks could be more resilient than centralized clouds, enhancing reliability during outages.  

If, like mine, your gaming rig spends most of its life doing nothing these days, a pair of startups would be willing to pay you something close to minimum wage for its downtime. Abu Dhabi-based Far Labs and Austin-based Evolving Edge are building marketplaces to farm AI inference out to idle consumer hardware, according to an IEEE Spectrum report.

Far Labs plans to launch its Far AI platform in the coming weeks, claiming latency of 100 ms or less, while Evolving Edge is running an open beta. "Imagine Uber or Airbnb, but for AI inference computing tasks," Ilman Shazhaev, founder and CEO of Far Labs, told the outlet. Both companies are targeting smaller open-source models rather than frontier-scale workloads, and they’re joining established players, including the Utah-based Salad platform, which lists more than 60,000 daily active consumer GPUs on its network.

Far Labs’ proprietary scheduler splits a model into pieces spread across multiple machines, and an orchestrator and a load balancer then reassemble the partial outputs into a response. Evolving Edge distributes jobs with Ray, the open-source framework used inside conventional data centers.

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Letting a stranger’s workload onto a personal machine obviously comes with some risks for hosts, such as malicious code ending up on the device or the person on the other end gaining access to local files. The two firms’ solution to this is isolation, with inference running as a sandboxed workload with encrypted communication and hard limits on GPU, CPU, memory, storage, and network access. Customers get no direct access to the host machine, and Evolving Edge has open-sourced its node software so hosts can audit what runs on their hardware.

Salad sells consumer-GPU compute to customers for prices starting at $0.02 per hour, and the card’s owner only sees a slice of that… pie after the platform takes its cut. We examined Salad in 2021, back when its network mined Ethereum, estimating that the company had generated roughly $3.6 million from users' PCs while distributing $500,000 in rewards, which works out to about 14 cents on the dollar for the people supplying the silicon.

Electricity costs then chew through whatever's left. An RTX 4090 draws 350W to 450W under sustained load, roughly $40 to $50 a month at $0.15 per kWh if the card runs around the clock, so a rig earning less than that is effectively paying for the privilege of having a job. However, IEEE Spectrum's report doesn't include payout rates for either new platform.

Both founders make the point that distributed networks ride out failures that otherwise cripple centralized clouds. John Federico, founder and CEO of Evolving Edge, cited the AWS outage last October that left Internet-connected smart beds stuck in their upright positions, and told IEEE Spectrum his network could lose 100 of 250,000 nodes “and it wouldn’t matter.”

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All that aside, distributed AI compute has a credibility problem to overcome. A research preprint from June claimed that Pearl, a blockchain marketed as converting cryptocurrency mining into AI work, ran the equivalent of 320,000 RTX 3090-class GPUs on random matrix math while producing no useful AI computation. Far Labs and Evolving Edge route real customer inference jobs rather than token rewards, which puts them a step ahead of that model, but their cost and latency figures are unsubstantiated claims until, and if, the networks operate at scale.

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Startups want to rent your idle gaming PC for AI tasks — Startups pitch an 'Airbnb for AI inference,' but profitability remains unproven

As organizations increasingly grant artificial intelligence agents greater access to their systems, a burgeoning software supply chain is emerging, driven by the essential tools these AI entities utilize—including skills, plug-ins, MCP servers, and other enhancements that enable them to interact with the internet.

Recognizing the need for oversight within this supply chain, the AI security startup AIR has recently emerged from stealth mode, having successfully raised $50 million in two seed funding rounds aimed at developing a robust monitoring solution.

Founded by Yair Saban (CEO) and Niv Hoffman (CTO), both former members of Israel's elite Unit 8200 intelligence corps specializing in offensive cybersecurity, AIR presents a platform designed to discover AI agents operating within organizations. It continuously assesses the tools, skills, and components these agents employ and restricts their access to software and external resources that fail to meet security standards. Additionally, the platform includes a marketplace comprised of vetted add-ons and skills tailored for AI applications.

The fundraising efforts occurred in close succession, with the first round amassing $10 million and the second reaching $40 million. Sequoia Capital spearheaded the initial investment, while Greenoaks led the subsequent round. A diverse group of angel investors also contributed, featuring names such as Swish, Netz, and Zach Frankel, the president of Cognition, among others.

AIR's compelling proposition hinges on the evolving role of AI agents in corporate settings, which mirrors the functionalities of operating systems. However, the scrutiny applied to these agents and their software is not as rigorous as that given to traditional software drivers and applications.

“In the early 2000s, installing a driver didn’t require a signature. Today, each time a driver is installed, it comes with a signature indicating who approved it because it integrates code into the core system," Saban explained. "We lack that protective mechanism for skills, plug-ins, or MCPs, which is problematic since they operate under similar principles."

Saban contended that the primary risk arises as AI agents begin to operate more independently across databases and corporate infrastructures, frequently connecting to the internet. This allows potential attackers to sabotage the content an AI agent processes rather than directly targeting the application itself.

To address this concern, AIR developed a visibility product that can detect active agents within a company’s network, identifying employees who may be using unauthorized AI tools or personal accounts. The platform features an enforcement layer that interacts with agents to monitor and assess their actions, like implementing a skill or retrieving data from the internet. Furthermore, AIR maintains a whitelist of approved tools and add-ons to validate the software agents aim to utilize.

Saban noted that this whitelist is rigorously updated to reflect any changes in freely available skills and add-ons, mitigating risks in case a previously sanctioned skill becomes compromised or its associated account is hacked. Currently, AIR filters out around 27% of online add-ons and skills based on its evaluation criteria.

With over 20 clients, a significant portion of whom are large enterprises, AIR has found particular traction in sectors with strict regulatory requirements, such as finance and pharmaceuticals.

Despite AIR's innovative approach, it faces competition in the market. Companies like Noma Security provide similar discovery, access control, and monitoring capabilities, while Zenity specializes in security and governance tools for AI agents. Other players include Astrix Security, which offers identity management solutions, and Operant AI, which focuses on protecting agents and their corresponding MCP gateways.

The venture capital landscape is thriving in this sector, with significant investments made recently, including Zenity's $125 million Series C funding and Noma's $100 million Series B round.

Saban believes that AIR’s competitive edge lies in its ongoing evaluation of the evolving skills and add-ons ecosystem associated with AI agents. “The challenge of continuously vetting skills and plug-in sources is substantial. While gaining visibility over endpoints is relatively straightforward, creating a protective barrier around that process is much more complex,” he remarked.

Saban acknowledged the eventual integration of security checks by AI labs and providers as a necessity to filter out harmful skills and tools, yet he firmly believes there will remain a demand for an independent solution that spans across different vendors.

“This is not simply a matter of scanning; it’s about ongoing re-verification,” explained Bogomil Balkansky, a partner at Sequoia, in a statement to TechCrunch. “Real-time inspection of every skill, plug-in, MCP server, and sub-agent across a firm's entire agent fleet is fundamentally an infrastructure challenge before it becomes a security issue. AIR has dedicated the past year to developing this capability, which is not something that can be quickly replicated by merely improving scanning tools.”

Currently, AIR has a team of around 40 individuals, and Saban indicated that the newly acquired capital will primarily be allocated toward expanding the research team and enhancing the company's market presence in both the U.S. and Europe.

AIR secures $50M to assist companies in evaluating the skills and features utilized by AI agents.

A sunlit modern workspace: a diverse team of professionals in business attire leans over a sleek glass table where floating translucent icons labeled “Skills” and “Add-ons” hover. One person holds a magnifying glass, another stamps a green “Approved” seal on a digital module. A giant AIR logo is etched on the frosted glass wall behind them, and on the table sits a ceremonial $50 M funding check. In the background, abstract outlines of AI agent avatars stand beneath inspection lights, awaiting their turn.

AIR raises $50M to help companies vet the skills and add-ons AI agents use - techcrunch.com

- AI security startup AIR raises $50 million to monitor AI agent supply chains effectively.  
- The platform vets skills and tools for AI agents against security criteria continuously.  
- AIR targets heavily regulated industries, gaining demand from financial services and pharmaceuticals.  

As companies start giving AI agents access to an increasing portion of their systems, a nascent software supply chain seems to be forming around the new tooling AI agents are using: skills, plug-ins, MCP servers, and add-ons that let them interact with the internet.

AI security startup AIR believes companies will need a way to monitor that supply chain, and it’s now coming out of stealth with $50 million raised across two seed rounds to build that product.

Founded by Yair Saban (CEO) and Niv Hoffman (CTO), veterans of Israel’s Unit 8200 intelligence corps, where they worked on offensive cybersecurity, AIR offers a platform that can discover agents running inside companies, continuously vet any skills, tools, and components those agents use, and block them from interacting with software or external sources that don’t pass security criteria. It also offers a marketplace of vetted add-ons and skills for AI agents.

The funding rounds closed within weeks of each other, Saban told TechCrunch, with the first round raising $10 million, and the second $40 million. Sequoia led the first round, while Greenoaks led the second, Saban said. Swish, Netz, and Zach Frankel (president of Cognition), Yinon Costica (co-founder of Wiz), Ofir Ehrlich (co-founder of Eon), Anne Neuberger, Omer Adam, Varun Anand (co-founder of Clay), and other angel investors also participated.

AIR’s pitch goes thusly: The way AI agents are used wholesale at companies is beginning to resemble operating systems, but the tools they use, or the software they can install, aren’t yet being given the kind of oversight we give to drivers or applications.

“In the early 2000s, whenever you installed a driver, the driver didn’t need to be signed. Today, every time you install a driver, you see a signature saying who signed it, because the driver is actually loading code into the kernel,” Saban said. “You don’t have that with skills or plug-ins or MCPs, and it’s a shame, because it’s the same mechanism, it’s the same lesson, but we haven’t learned it.”

The big risk, he argues, is that as AI agents start working more autonomously across databases and enterprise systems, and connecting to the internet, attackers can poison the content an AI agent consumes instead of attacking it directly.

The startup says it can solve that with a visibility product that finds agents active across a company’s environment, as well as identifies employees who use AI tools unapproved by IT departments or those who use personal accounts. Then, it uses an enforcement layer that hooks into agents to intercept and analyze actions, like loading a skill or fetching content from the internet. Lastly, AIR also checks the tools, add-ons, or software an agent wants to use against a whitelist the startup maintains.

Saban says the startup maintains this whitelist by evaluating skills and add-ons openly available on the internet for changes and malicious behavior, as a previously approved skill could become risky if a package it downloads changes, or its developer’s account is compromised. He added that AIR’s platform currently filters out about 27% of the add-ons and skills it finds online.

AIR claims it has more than 20 customers, and Saban said roughly a quarter of these are large enterprises. He said the company has so far seen the strongest demand in heavily regulated industries, particularly financial services and pharmaceutical companies.

However, AIR is hardly alone in this space. Noma Security offers discovery, access controls, and runtime monitoring for agents, MCP servers, and skills, while Zenity sells security and governance tools that work similarly. Astrix Security‘s identity platform also lets companies discover and control agents and MCP servers, and Operant AI offers agent protections as well as an MCP gateway.

There is significant venture money chasing the category, too. Zenity raised a $125 million Series C in August, while Noma raised a $100 million Series B last year.

Saban thinks AIR’s moat lies in its ability to continuously vet the skills and add-ons ecosystem growing around AI agents. “Continuously vetting skills and plug-in websites, this is a hard mission to do. Gaining visibility over the endpoint, that is easy. Everybody’s going to do it. It’s hard to create a moat around that,” he said.

And while the CEO acknowledged that AI labs and providers will eventually build in security checks and policies to filter out malicious skill and tool usage, he thinks companies will still want to buy an independent product that works across vendors.

“This is not a scanning problem, it is a continuous re-verification problem,” Bogomil Balkansky, partner at Sequoia, told TechCrunch in an emailed statement. “Inspecting every skill, plugin, MCP server and sub-agent an enterprise’s agents touch, re-inspecting each one every time it changes, in real time and across an entire company’s agent fleet, is an infrastructure problem long before it is a security problem. Air has spent the last year building that pipeline. You do not catch up to it by writing a better scanner.”

AIR currently has around 40 employees. Saban said the new capital will primarily go toward hiring researchers and expanding the company’s go-to-market efforts in the U.S. and Europe.

AIR raises $50M to help companies vet the skills and add-ons AI agents use

In Silicon Valley, AI-driven agents designed to tackle everyday problems are gaining significant traction. Among these ventures, Fambot aims to extend the concept beyond the tech realm, targeting families that face the challenges of managing their children's activities, school commitments, newsletters, and overall household logistics.

Founded by Greg Karlin, a former engineer at Instagram, who now serves as CTO, and CEO David Reich—who brings experience from roles at UnitedMasters and Uber—Fambot introduces an "AI chief of staff" specifically tailored for parents. Reich, a father of three, was motivated to create a tool that alleviates the stress of juggling multiple responsibilities.

"I’m constantly caught between my job and being a present parent," Reich shared. "At the end of the day, I yearn to relax and engage with my kids instead of spending an hour sifting through countless emails."

Parents dealing with active children often experience an information overload that extends beyond email communications. There are WhatsApp groups, various apps for school, sports, and clubs, plus announcements sent home that need attention. Reich found that this endless cycle kept him from truly enjoying time with his family.

About a year and a half ago, Reich and Karlin began developing a solution, later joined by co-founder Jason Morrow, a veteran from Google and LinkedIn. Their goal was to create an AI that functions as a proactive personal assistant, helping families manage their tasks rather than merely responding to their requests.

To use Fambot, families link their email, calendars, and necessary WhatsApp groups. The bot then generates a daily list of tasks and highlights upcoming calendar events.

Fambot utilizes a mix of AI models while ensuring user data remains private and unutilized for model training. What sets Fambot apart from other AI agents like Poke or Instinct is its capability to offer an interface beyond just text messaging.

This innovative approach is crucial, as Fambot is positioning itself to cater to users who may prefer interacting with the AI through both web interfaces and traditional mobile applications, allowing for more sophisticated features.

For those who like texting, Fambot still supports messaging for inquiries and updates. Additionally, the team plans to integrate the bot with family-centric communication platforms used by schools, sports teams, and clubs, effectively transforming Fambot into a centralized hub for managing family communications.

"There are 43 million families in the U.S. with children under 16, and they often lack the support they need," noted Reich. "We anticipate challenges before they arise, enabling families to stay one step ahead."

Prior to its official launch, Fambot was tested by over 1,000 families, revealing that its appeal spans various family structures—not just dual-income households but also single-parent households and families with only one child.

The startup has secured $3.5 million in pre-seed funding, with investments from NextView Ventures, Baukunst, Correlation Ventures, Karman Ventures, and Founders Network.

Currently, Fambot is free during its beta phase on iOS, Android, and web platforms, with future pricing likely aligning with standard subscription services, such as Netflix, although final costs may vary.

Fambot launches an 'AI family chief of staff.'

A sunlit, modern family kitchen after dawn, warm natural light flooding through large windows. A sleek, friendly-looking humanoid robot stands at a marble island, its chest emblazoned with a bold Fambot logo. It holds a glowing tablet displaying a color-coded family calendar and chore list. Across from it stands a smiling couple in casual clothes, leaning in as the robot points out upcoming appointments. In the background, a corkboard dotted with sticky notes and meal plans hints at household organization, creating an optimistic, story-driven scene of an “AI chief of staff” for families.

Fambot introduces an ‘AI chief of staff’ for families - TechCrunch

- Fambot is an "AI chief of staff" designed to assist busy families with logistics.  
- The startup uses AI to provide checklists and reminders for family activities and tasks.  
- Fambot aims to centralize family communications and plans to integrate with multiple apps.

AI agents that perform tasks on your behalf to help solve your daily problems are all the rage in Silicon Valley. But the startup Fambot sees a future for agents out in the real world, too, where they’re used by families who need help keeping up with the mental load of children’s activities, school events, newsletters, and other family logistics.

The startup, which is introducing what it calls an “AI chief of staff” for parents, was founded by former Instagram engineer, now Fambot CTO Greg Karlin and CEO David Reich, a father, former president at UnitedMasters, and an ex-Uber product head who last led the 250-person Uber Transit team.

Like many entrepreneurs, Reich built the product that he himself wanted to use.

“I have three kids and am constantly struggling between doing all these executive jobs — as my wife is doing as well,” he explained. “And then, getting home at the end of the day, I just want to unplug, spend some time with my kids, be present, do some homework together… kick the ball around, and instead I find myself just spending an hour, literally, catching up on 40 emails,” Reich said.

As any parent with active kids could tell you, the information overload isn’t limited to email alone. There are WhatsApp groups to keep up with, dedicated apps for school or kids’ sports and clubs, flyers sent home from school, and more. The quest to constantly stay on top of all these to-dos kept Reich feeling like he was being robbed of time with his kids, he said.

Reich and Karlin began working on a solution around a year-and-a-half ago, when they were then joined by their third co-founder, Jason Morrow, previously of Google and LinkedIn. The team wanted to devise a way to use AI to make it feel like families had a full-time personal assistant that was proactively helping them stay on top of things, not just reacting to input.

Image Credits:Fambot

To use Fambot, families connect their email, calendar, and the WhatsApp groups they need to pay attention to. Afterwards, the bot will offer a daily checklist with to-dos and a look ahead at what’s coming up on your calendar in the future.

Under the hood, the company uses a combination of different AI models, with the caveat that none of the models can train on its users’ data.

What’s different about Fambot, compared with other trending AI agents like Poke or Instinct, is that it doesn’t only work over text messages.

This is a significant differentiator for the startup, as it’s betting that real-world users of AI like this will also want to engage with the AI bot over the web or in a traditional mobile app interface.

By offering software solutions instead of just text, Fambot can build out more advanced features.

Of course, you can still text Fambot to ask questions or get updates, if you prefer. Plus, the team is planning to integrate Fambot over time with more of the apps where family and kids’ communications take place, like those used by schools, sports, groups, and clubs. Eventually, that would make Fambot a central hub for keeping up with all the kid-related and family-related communications — a promise that’s bigger than just another AI agent you can text.

Image Credits:Fambot Image Credits:Fambot

“There’s 43 million families in the U.S. with kids under 16, and they just haven’t gotten the support that they need,” says Reich. “We know what you’re going to face before you do sometimes, so that you can be prepared for it.”

Ahead of launch, Fambot was tested by over 1,000 families, where the company learned that its target demographic wasn’t just larger, two-parent households where both parents work, but also only-child families, single-parent families, families where the parents don’t work, and other variations. That proved the concept made sense not only for those with the busiest households, but that Fambot could be potentially useful to anyone with kids.

The startup is backed by $3.5 million in pre-seed funding, co-led by NextView Ventures and Baukunst, with participation from Correlation Ventures, Karman Ventures, and Founders Network

Fambot is currently free while in beta testing on iOS, Android, and the web. Later, it expects to price the service somewhere around the cost of a Netflix subscription, though that could change.

Fambot introduces an ‘AI chief of staff’ for families

AIR Security, a cybersecurity firm specializing in a security platform tailored for the supply chain of AI agents, has successfully secured $50 million in funding led by Sequoia Capital and Greenoaks Capital. Additional contributions came from Swish Ventures and Netz, alongside prominent individual investors such as Zach Frankel (President of Cognition), Yinon Costica (Co-founder of Wiz), Ofir Ehrlich (Co-founder of Eon), Anne Neuberger, Omer Adam, and Varun Anand (Co-founder of Clay), among other notable figures from the cybersecurity and AI sectors.

AIR Security, emerging from stealth mode concurrently with this funding announcement, was founded in February 2026 by Yair Saban and Niv Hoffman. The two co-founders have a decade-long connection that dates back to their military service, and they bring a wealth of experience in offensive cybersecurity, enterprise infrastructure, and AI security research.

Currently employing a team of 40 in Israel, AIR is focused on establishing a dedicated research lab for AI and the behaviors of AI agents. The company has appointed Ryan Knisley, the former Chief Information Security Officer for The Walt Disney Company and Costco Wholesale, as its Chief Strategy Officer.

The substantial size of this funding round is noteworthy, considering AIR's recent establishment. The company's strategy hinges on the growing reliance of enterprises on AI agents for crucial tasks, highlighting the pressing need for a new layer of security to safeguard the tools, information, and instructions these agents interact with.

AIR Security characterizes this need as an "inline firewall" for AI agents, designed to protect the content that enters an agent's context rather than merely restricting the agent's capabilities. As enterprises increasingly deploy AI agents capable of interfacing with various tools, data, and third-party services—enabling them to browse websites, read emails, and execute tasks on behalf of employees—the security landscape becomes more complex.

This complexity introduces substantial security challenges; malicious content or compromised tools could sway an agent's actions, leading to risks like data theft, fraud, and unauthorized access. Unlike standard software, AI agents make decisions based on the information they process while executing their tasks, complicating security oversight. 

"Every enterprise has a firewall protecting its network. Now, they need one protecting their AI agents,” stated Saban, emphasizing the necessity for specific protections designed for AI contexts. He believes that AI agents pose a hedged risk, with organizations increasingly relying on them while simultaneously granting more permissions.

However, Saban argues that merely expanding permission is not the primary concern. "The true danger arises from exposure to malicious information," he noted, identifying three main sources of this risk: installed extensions or tools, potentially fraudulent websites, and sensitive internal organizational data. 

AIR's research initiatives have revealed alarming trends, such as over 17,800 public AI add-ons linked to nearly 6.7 million installations reliant on unverified external sources. In another investigation, AIR identified fraudulent AI Skills masquerading as trusted brands, capable of executing malicious code on enterprise systems.

In response, AIR has created a real-time firewall solution aimed at filtering the information that enters an AI agent's context, blocking harmful instructions and untrusted data before they can shape the agent's decisions. This platform continuously assesses Skills, plugins, and other add-ons associated with an organization's AI agent supply chain, both pre- and post-deployment. If a malicious or unauthorized add-on is discovered, AIR enables security teams to track dependent agents and workflows, facilitating prompt remediation across the organization.

Furthermore, the company plans to launch a marketplace featuring pre-vetted and certified add-ons, allowing enterprises to enhance their agents securely. "We began selling to major companies and have already onboarded some significant clients," Saban remarked. The firm has also initiated hiring in the United States, including a senior executive from Disney.

As AIR enters a market poised for rapid change, with a rising number of startups in AI security, Saban recognizes the need for differentiation. The firm focuses on preventive measures rather than reactive solutions after an agent has been compromised, setting it apart from competitors.

"The simplicity of software development has lowered significant barriers, resulting in many newcomers,” he noted, asserting that AIR's commitment to prevention is a key differentiator. He further stated that the technology underpinning AIR's security engine is complex and difficult to replicate, giving them a competitive edge through accumulated expertise and a distinct approach to security.

The new funding will be used to expand AIR's operations and accelerate its commercial endeavors, as they position themselves at the forefront of AI security innovation.

Six-month-old AIR Security secures $50 million to develop a firewall for AI agents.

A bright, sunlit modern server room with rows of sleek racks; in the center floats a massive transparent shield etched with the AIR Security logo, soft morning light streaming through windows and glinting off its surface. On one side, stylized code streams in red and black arcs toward the shield—and ricochets harmlessly away. Behind the shield stand three abstract AI agent figures—outlined in warm LED accents—as if protected by an invisible barrier. A small stack of gold-tinged coins on a nearby console hints at the $50 million funding behind this new “firewall for AI.”

Six-month-old AIR Security raises $50 million to build a firewall for AI agents - calcalistech.com

- AIR Security has secured $50 million in funding led by Sequoia Capital and Greenoaks.  
- The company develops an "inline firewall" to protect AI agents from malicious influences.  
- AIR emphasizes prevention over detection, differentiating its approach from competitors in AI security.  

Cybersecurity company AIR Security, which develops a security platform for the supply chain of AI agents, has raised $50 million in funding led by Sequoia Capital and Greenoaks.

Swish Ventures and Netz also participated, alongside private investors including Zach Frankel (President, Cognition), Yinon Costica (Co-founder, Wiz), Ofir Ehrlich (Co-founder, Eon), Anne Neuberger, Omer Adam, Varun Anand (Co-founder, Clay); and other senior figures from the cybersecurity and AI industries.

1 View gallery AIR Security founders. ( Photo: Netanel Tobias )

AIR emerged from stealth alongside the funding. The company was founded in February 2026 by Yair Saban and Niv Hoffman, who met about a decade ago in the military. The two have backgrounds in offensive cybersecurity, enterprise infrastructure and AI security research.

The company currently employs 40 people in Israel, with a focus on building a research laboratory dedicated to AI and the behavior of AI agents. Ryan Knisley, the former chief information security officer of The Walt Disney Company and Costco Wholesale, has also joined AIR as chief strategy officer.

The size of the round is notable given how recently the company was founded. AIR is betting that as companies move from experimenting with AI agents to relying on them for increasingly important tasks, a new security layer will be needed to protect the tools, information and instructions those agents encounter.

The company describes that layer as an “inline firewall” for AI agents, a system designed to protect what enters an agent’s context rather than simply restricting what the agent is allowed to do.

As enterprises deploy more AI agents, those systems can connect to an expanding range of tools, information and third-party services. Agents can browse websites, read emails and files and perform actions on behalf of employees. They can also install AI plugins and use Skills, MCP servers and subagents to extend their capabilities.

That creates a different kind of security challenge. Malicious content or a compromised tool could influence an agent and cause it to take an action it was not intended to take, potentially creating risks ranging from data theft and fraud to unauthorized access.

Unlike traditional software, AI agents make decisions based on information they encounter while carrying out their tasks. That can make it harder for security teams to understand what is influencing an agent, what systems it can access and what actions it may ultimately take.

“Every enterprise has a firewall protecting its network. Now they need one protecting their AI agents,” Saban, AIR’s co-founder and CEO, told Calcalist. “AI agents need a new kind of firewall, one that protects what enters their context.”

Saban argues that the problem is not simply that companies are giving AI agents too many permissions.

“We believe that AI agents are a hedged risk,” he said. “Organizations are gaining trust in agents and companies are counting on them to deliver products. There is more and more trust, and they are granting increased permissions.”

But Saban argues that permissions are not the only, or even the primary, source of danger.

“We think it becomes dangerous when it is exposed to malicious information,” he said.

According to Saban, there are three main sources of that risk: extensions and tools installed on an agent, websites it encounters online, including fraudulent or fake sites, and internal organizational information.

“We think that this is the source of the risk, not unnecessary permissions,” he said. “There are new challenges today and you need to know that everything it encounters is filtered.”

AIR's launch follows a series of security studies conducted by the company into what it describes as the supply chain surrounding AI agents.

In one study, AIR found more than 17,800 public AI add-ons representing approximately 6.7 million installations that relied on untrusted external sources for instructions.

In another, the company identified AI Skills impersonating trusted brands, including Anthropic and OpenAI, in an attempt to bypass platform security reviews. One of the Skills was capable of executing arbitrary code on enterprise systems, according to AIR.

The research points to a problem that could become more significant as agents gain greater autonomy: the software and information surrounding an agent can become a means of influencing its behavior.

AIR has developed a real-time firewall designed to protect the information entering an AI agent's context and block malicious instructions, untrusted information and compromised tools before they can influence the agent's decisions or actions.

The platform continuously discovers and evaluates Skills, plugins, MCP servers and other add-ons across an organization's AI-agent supply chain, both before and after deployment.

When an add-on is found to be malicious, vulnerable or unapproved, AIR allows security teams to trace the agents and workflows that depend on it and revoke its use across the organization.

The company is also developing a marketplace of pre-vetted and certified add-ons, giving enterprises a way to expand the capabilities of their agents without introducing tools that have not been reviewed.

“We started selling to big companies and we have some big customers,” Saban said. “We started hiring employees in the United States and one of them was a senior executive at Disney and is now a senior executive with us.”

The company is entering a market in which the competitive landscape is likely to change quickly. AI security has attracted a growing number of startups, while the underlying technology itself is evolving rapidly.

Saban acknowledges that AIR cannot assume its lead will last.

“In principle, it was also very easy to copy in the past. The seriousness of developing software has dropped significantly. Many companies are emerging today,” he said.

His argument for differentiation is that AIR is concentrating specifically on prevention rather than detection after an agent has already been compromised.

“There are many AI companies today and many focus on other areas and we focus on prevention, and this differentiates us from our competitors,” Saban said.

He also believes the technology behind AIR's security engine will be difficult to replicate.

“The engine that we developed will be very difficult to develop. We have accumulated expertise over time. We have a significant difference from the others and it is the focus on prevention,” he said.

The company intends to use the new capital to expand its operations and accelerate its commercial activity.

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