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Nvidia Stock: Reasons Behind 15% Price Hike and Investment in AI Startups

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Nvidia Stock: Why It May Be Raising Prices 15% and Funding AI Startups - Barron's

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Nvidia Stock: Why It’s Raising Prices 15% and Funding AI Startups

General Intuition, a New York-based startup focused on developing a foundational model for generalized AI agents capable of navigating both space and time, is currently in discussions to secure funding that would elevate its pre-money valuation to $6 billion. Notable new investors in these negotiations include Valor Equity Partners, Point72 Ventures, and Seven Seven Six, as reported by sources familiar with the situation.

Current backers, such as Khosla Ventures and General Catalyst, are also expected to take part in this funding round. This capital infusion follows a recent successful raise of $320 million at a $2.3 billion valuation, underscoring the startup’s rapid growth within the burgeoning field of physical AI.

The latest developments align with prior reports regarding General Intuition, which has emerged as a leading player in the creation of innovative AI solutions. The company was founded by CEO Pim de Witte last October, originally as a spinoff from his video game clip-sharing platform, Medal. General Intuition leverages extensive gameplay data—including hundreds of millions of hours of recorded action labels, which detail player inputs and timings—as a foundational dataset for its model.

In a recent statement to TechCrunch, investor Vinod Khosla highlighted the significance of these action labels in fostering what he describes as the “emergence of intuition.” This pertains to the model's capability to generalize across various tasks not specifically included in its training.

General Intuition is in the process of finalizing this funding round, which is reportedly oversubscribed, reflecting strong interest from investors. The company plans to utilize the new capital to refine its general model, particularly focusing on robotic applications. This includes investments in computing infrastructure—having partnered with CoreWeave—and increasing its workforce.

Valor Equity Partners, known for its support of SpaceX, is poised to enter the AI domain with this investment, marking a significant moment as it would be the first AI lab the fund has engaged with since backing SpaceX.

Further updates on this developing story will be provided as they become available.

Valor and Point72 support General Intuition with a $6B valuation as the AI startup expands into robotics.

A sunlit robotics workshop bathed in warm natural light, sleek robotic arms assembling a cutting-edge humanoid robot atop a wooden workbench; on the white wall behind, a large General Intuition logo, flanked by gold-plated investor plaques labeled Valor and Point72, and a discreet metal plate engraved “$6 B” in the foreground to underscore the startup’s new valuation.

Valor, Point72 back General Intuition at $6B valuation as AI startup pushes into robotics - TechCrunch

- General Intuition is raising funding at a $6 billion valuation from notable investors.  
- The company recently secured $320 million at a $2.3 billion valuation.  
- Funds will improve general models with a focus on robotic embodiments and infrastructure.  

New York-based General Intuition, the startup building a foundation model that trains generalized AI agents to move through space and time, is in talks to raise funding at a $6 billion pre-money valuation from new investors including Valor Equity Partners, Point72 Ventures, and Seven Seven Six, according to sources familiar with the matter.

Existing investors including Khosla Ventures and General Catalyst are also participating in the round. The fresh funds would come just weeks after General Intuition raised $320 million at a $2.3 billion valuation.

The news confirms earlier reporting on the deal for what is becoming one of the hottest startups tackling physical AI.

CEO Pim de Witte spun out General Intuition last October from his video game clip-sharing platform Medal, using its hundreds of millions of hours of gameplay and “action labels” — records of which buttons a player pressed and when — as an initial dataset.

First sneak peak in the WSJ on how GI’s large action models work! https://t.co/6fuOcu9fkb — Pim de Witte (@PimDeWitte) August 21, 2026

Investor Vinod Khosla recently told TechCrunch that he believes those action labels will be a key part of the “emergence of intuition,” or the ability for a model to truly generalize across tasks that it wasn’t explicitly trained on.

General Intuition is still finalizing the round, and a source close to the deal said that it is oversubscribed as the startup continues to field interest from investors. The company intends to use the funds to focus to improve its general model with a focus on robotic embodiments. That means spending more on compute infrastructure (the company has a partnership with neolab CoreWeave) and hiring more talent.

Valor Equity Partners is known for backing SpaceX. TechCrunch has reached out to confirm its investment in General Intuition, which would be the first AI lab the fund has invested in since SpaceX.



This story is developing. Please check back in for updates.

Valor, Point72 back General Intuition at $6B valuation as AI startup pushes into robotics

In Salt Lake City, the University of Utah has unveiled a groundbreaking supercomputer named Redtail, now recognized as one of the top 160 fastest supercomputers globally. Within its first month of operation, Redtail achieved an impressive 5th place among public universities in the U.S. on the Top500 list and secured the 76th position on the Green500, which ranks the most energy-efficient supercomputers.

This advanced computational system, which boasts a $50 million price tag, was financed through a collaborative effort involving the state of Utah, the Huntsman Family Foundation, Hewlett Packard Enterprise, and NVIDIA. It aims to provide vital computational resources for researchers, students, and businesses throughout Utah, facilitating the kind of AI-driven projects that require substantial processing power.

Manish Parashar, the university's inaugural chief AI officer, expressed enthusiasm about the potential of this new technology. “It shows that our state, faculty, students, researchers, and entrepreneurs have access to world-class technology,” he remarked, emphasizing the competitive edge it provides.

The initial interest in Redtail is significant, with researchers already applying its capabilities to diverse projects like climate modeling, air quality improvement, drug discovery, aerospace engineering, and notably, creating digital replicas of human vascular systems aimed at enhancing precision medicine. “This project addresses how to craft a digital twin of a human vascular system for more customized and effective treatment,” Parashar explained.

Coinciding with Redtail's introduction, the University of Utah was invited to join a National Science Foundation network dedicated to AI-driven Cloud Laboratories. Parashar mentioned that the Cloud Lab seeks to automate research processes, allowing scientists to collaborate regardless of their physical locations. Redtail’s robust processing abilities will be instrumental in developing models and AI functionalities for such initiatives.

This investment aligns with a broader strategy in Utah, where efforts to strengthen AI capabilities have intensified over the past year. The state has launched a $100 million Pro-Human AI Initiative, focusing on AI applications for education, air quality, and wildfire management. Additionally, the establishment of an $18.6 million Health AI Vault is enhancing research into cancer and medical AI. Recently, the university was recognized as a national leader in AI, ranking among the top 5% of educational institutions for its AI-related efforts.

The financial investment landscape also reflects this growth. Local AI startup Jump raised $80 million earlier this year, while Databento attracted $97 million in its Series B funding. Zanskar, specializing in geothermal energy through AI, secured $115 million. Collectively, Utah's AI sector has seen an influx of hundreds of millions in venture capital in 2026.

Jump's founder, Parker Ence, credits local investors with significantly contributing to his company’s success. “The funding we received from regional firms like Sorenson and Pelion was crucial for our growth,” he shared. He also highlighted the talent capable of competing with coastal companies, asserting that his entire executive team is composed of Utah locals.

Additionally, the Silicon Slopes community has initiated Start School, a program for aspiring entrepreneurs emphasizing that modern AI tools enable solo founders to launch successful ventures without needing venture capital.

On the regulatory front, Utah is making strides in AI governance, distinguishing itself from other states still grappling with regulatory frameworks. Margaret Woolley Busse, the executive director of the Utah Department of Commerce and the architect of the Office of AI Policy, noted a surprising surge of interest in healthcare-related AI innovations. “Business innovators here are developing transformative AI solutions that could greatly enhance residents' lives,” she mentioned, pointing to the state's proactive regulatory approach.

Utah has enacted several AI-specific laws, including mandates for consumer awareness when interacting with AI in sensitive contexts, protections against unauthorized deepfakes, and inclusive policies for AI-generated content.

As for businesses navigating the AI landscape, Kavita Ganesan, founder of Opinosis Analytics, an AI consultancy in Salt Lake City, noted a shift in focus among companies. While enthusiasm for AI was high, discussions have evolved into more practical considerations on implementing the technology effectively. “Organizations are not struggling with access to supercomputers or regulatory frameworks,” she observed, emphasizing that many are still exploring foundational aspects, such as identifying suitable use cases for AI and integration into existing operations.

Despite the notable advancements, Parashar acknowledged that Utah's journey in AI is just beginning. “While our progress is commendable, we are still at an early stage,” he stated, urging a forward-looking approach to prepare for future developments in AI.

The University of Utah is set to host its annual One-U Responsible AI Initiative symposium on October 6, further underlining its commitment to responsible AI advancement and collaboration.


Exploring Utah's expanding investment in AI, from supercomputers to startups.

Bright midday sunlight floods a sleek innovation hub: on the left, engineers monitor towering supercomputer racks glowing softly behind a glass wall; on the right, a small team of entrepreneurs huddles over laptops around a wooden table brainstorming. A single Utah state flag hangs prominently on the wall, casting a warm glow across the scene.

From supercomputers to startups: Inside Utah's growing bet on AI - KSL News

- The University of Utah launched the Redtail supercomputer, ranking 5th among U.S. public universities.  
- Redtail, funded by a $50 million partnership, supports advanced AI research and applications statewide.  
- Utah's proactive AI regulations aim to ensure public trust and improve resident lives.  

SALT LAKE CITY — The University of Utah just turned on a supercomputer that ranks among the 160 fastest in the world.

Redtail, as it's called, also placed 5th among U.S. public universities on the Top500 list and 76th on the Green500, which tracks the world's most energy-efficient machines. All of this in its first month of operation.

The system cost $50 million, funded through a partnership between the state of Utah, the Huntsman Family Foundation, Hewlett Packard Enterprise and NVIDIA. It's designed to give researchers, students, and eventually businesses across the state access to the kind of computing power that serious AI work requires.

"It demonstrates that the state, the faculty, the students, the researchers, the entrepreneurs have access to state-of-the-art technology that is on par with anybody else in the world," said Manish Parashar, the university's first chief AI officer. "And they can bring that to their work."

The projects already lining up give a sense of the scale. Through a Redtail challenge designed to attract early users, researchers are applying the system to climate modeling, air quality, drug design, aerospace engineering, and something Parashar is particularly excited about: building digital twins of human vascular systems for precision medicine.

"How do you build a digital twin of a human vascular system so that you can do more targeted precision treatments, treatments that are targeted to an individual, that can be more effective?" Parashar said. "These are the types of projects we are seeing emerge."

The same week Redtail earned its rankings, the university was also selected for a National Science Foundation network of AI-driven Cloud Laboratories. Parashar described the Cloud Lab as a way to automate research processes that traditionally require scientists to be physically in the room. The result is that researchers anywhere can participate in work that used to be limited by geography.

"Redtail provides the computational platform that can help build the models and the AI that can drive something like the Cloud Lab," he said.

The bigger picture

The infrastructure investment is significant on its own. But it fits into a pattern that's been building across Utah for the last year.

The state's $100 million Pro-Human AI Initiative, launched at the governor's level, continues to expand. New faculty have been brought in to focus on AI applications in education, air quality, and wildfire monitoring. An $18.6 million Health AI Vault is advancing cancer research and medical AI. And the university was recently evaluated as a national "trailblazer," ranking in the top 5% of academic institutions for its AI response.

The money side tells its own story. Jump, a Utah-based AI company, closed an $80 million growth round earlier this year. Databento, an AI-driven financial data firm, landed a $97 million Series B with more than $300 million in investor demand. Zanskar, an AI-native geothermal company, raised $115 million. Collectively, hundreds of millions in AI venture capital have flowed into Utah in 2026 alone.

Systems in the Redtail AI Factory, which will support research and innovation across Utah. (Photo: University of Utah)

Parker Ence, founder of Jump, said the local investing community played a real role in his company's growth.

"Taking investment from Sorenson and Pelion was a key early step for us that set us up for success in later fundraising rounds," Ence told me. "As a minor contributor to the Governor's AI Task Force, I've been impressed with the level of thought going into advancing economic opportunity for Utahns while balancing safety and pro-human outcomes."

He also pushed back on the idea that Utah companies need to recruit from the coasts.

"The idea that you have to go outside of Utah to attract stellar talent isn't true," he said. "Our entire exec team, which I would put up against any vertical-focused AI company, is all Utah-based."

Meanwhile, Silicon Slopes recently launched Start School, a new program for Utah entrepreneurs built around a single thesis: AI tools have lowered the barriers to starting a company to the point that solo founders can build viable businesses without venture capital.

The rules of the road

Utah has also been moving on AI regulation, an area where most states are still debating where to begin.

Margaret Woolley Busse, executive director of the Utah Department of Commerce and architect of the state's Office of AI Policy, told me the biggest surprise has been the level of interest in healthcare AI.

"Innovators doing business in Utah are actively working on transformative AI solutions that have the potential to significantly improve the lives of residents," Busse said. "The state recognizes the risks associated with these advancements and is taking a proactive role in overseeing regulatory sandbox pilots."

Utah already has several AI-specific laws on the books: a requirement that consumers be informed when they're interacting with AI in high-risk situations; protections against non-consensual deepfakes; libel and slander laws expanded to cover AI-generated content; and safeguards around mental health AI applications.

"Without adequate safeguards, public trust in AI technology will not develop, which could hinder its positive applications in various sectors across the state," Busse said.

What businesses are actually experiencing

The state-level numbers are big. But what does all of this actually look like for a Utah business trying to figure out AI?

Kavita Ganesan, founder of Opinosis Analytics, a Salt Lake City-based AI consultancy, works directly with small businesses, mid-sized firms, nonprofits and government agencies. She told me the conversation around AI has changed over the past year, but not in the direction most people assume.

Innovators doing business in Utah are actively working on transformative AI solutions that have the potential to significantly improve the lives of residents. –Margaret Woolley Busse

"The conversation has shifted from raw enthusiasm to implementing AI the right way," Ganesan said. "As teams become more familiar with the technology, they are seeking true expertise to implement reliable solutions, especially as market hype and low-quality providers create fatigue and disappointment in the field."

I asked her whether Utah's growing AI infrastructure, from Redtail to the Office of AI Policy to the venture funding, is making a practical difference for her clients.

She was direct.

"Most organizations are not held back by a lack of supercomputing power or state policy frameworks," Ganesan said. "They are still working through the foundational phases: trying to vet use cases, identifying real business opportunities, and figuring out how to integrate AI into existing workflows safely and effectively."

It's a reminder that the headline numbers and the day-to-day reality of AI adoption are still in very different places for most companies.

Still early

Parashar acknowledged that Utah's progress, while real, is still early.

"AI is a very fast-evolving technology, and I think we are still in early stages," he said. "We are doing a great job getting to the puck. I think now it's time to think about where the puck is going to be in three years and how do we get there ahead of time, so we're not surprised."

Utah is betting that preparation, not reaction, will separate the states that lead from those that follow. The state is investing in infrastructure, the talent pipeline, policy guardrails and business support before the full wave of demand arrives.

Whether that bet pays off will depend on how quickly the gap closes between the supercomputer in the university basement and the small business owner trying to figure out where AI fits into her Tuesday.

The University of Utah will host its annual One-U Responsible AI Initiative symposium on Oct. 6.

More on KSL

From supercomputers to startups: Inside Utah's growing bet on AI

For years, the process of updating financial software used for bookkeeping has monopolized the efforts of consultants. 

Nicolas Kopp, the CEO of Rillet, an AI-driven accounting startup, expressed this sentiment succinctly to Business Insider: "It's not enjoyable being a consultant implementing your third version of Oracle Fusion and watching three years slip away while you transform Excel spreadsheets and navigate an outdated system."

Oracle Fusion is a robust suite of cloud solutions utilized by large enterprises to oversee their financial and operational needs. The installation of such systems can demand extensive consulting resources, often spanning several years. Rillet aims to streamline this arduous process by leveraging artificial intelligence to maintain real-time financial records as transactions unfold.

Kopp summarized the startup's main goal as follows: "To minimize the time humans spend clicking through applications."

Rillet's rapid ascent also highlights a transformative trend in the consulting industry. With AI assuming a larger share of routine accounting responsibilities, firms are increasingly in search of professionals who possess specialized knowledge and the technical acumen to navigate AI technologies and large datasets.

Recently emerging from a period of secrecy, Rillet announced a significant $100 million Series C funding round at a valuation of $1 billion. This positions the company as a key player among a wave of startups challenging the entrenched enterprise resource planning (ERP) market. With a total funding exceeding $200 million, Rillet stands out as one of the most heavily financed companies offering an AI-augmented alternative to traditional financial software.

Currently, Rillet services over 600 clients across various sectors, including notable names such as Mercor, Neuralink, Temporal, and Skild AI. Interestingly, 40% of its clientele is drawn from industries beyond technology and AI, spanning healthcare, financial services, retail, and biotechnology. Half of its customers have transitioned from legacy ERP systems like NetSuite, Workday, Oracle Fusion, and Sage Intacct, while the remaining clientele has migrated from Intuit.

The evolution towards a more streamlined bookkeeping process is exemplified by Rillet's innovative approach. An analysis conducted by Andreessen Horowitz involving 56 of Rillet's customers revealed that 87% had less than 1% of bookkeeping entries pending for review at month’s end.

This development signals a broader transformation within the enterprise software landscape. Recent downturns among traditional software firms have been coined the "SaaSpocalypse," as advancements in AI prompt businesses to reconsider their investment in extensive software seats, questioning whether newer AI-native solutions can effectively replace them.

Kopp anticipates a shift in how companies procure software. He predicts that the traditional model of billing clients based on employee usage will soon become obsolete, as AI takes over much of the operational workload.

As the deployment of AI reshapes enterprise software operations, it also impacts the types of expertise consulting firms seek. Rillet recently formed a "corporate development alliance" with EY and collaborates with various consulting players like RSM and KPMG.

In the short term, Kopp sees a significant opportunity for consulting firms in areas like change management and system implementation. In the long run, he envisions leveraging years of accumulated accounting knowledge into "skill files, repositories, and agents" that can be integrated with AI systems such as Rillet’s.

"I believe there's substantial potential in developing these agents," Kopp stated. Already, Rillet is assisting a consulting firm in creating analytics and reporting agents for forecasting dashboards and tools for monitoring controls and risks, thereby simplifying the analysis of large datasets.

This shift is reshaping the human talent landscape, especially as the accounting sector continues to wrestle with a prolonged talent shortage.

"The demand for expertise is rising," Kopp noted. "AI levels the field, necessitating highly skilled accountants and accounting professionals within these firms. Otherwise, AI may end up serving as a substitute for their work." He foresees a trend where entry-level positions will increasingly be filled by AI over the next couple of years, creating fresh demand for specialized experts.

Simultaneously, there's a burgeoning category of tech-savvy, innovative workers eager to explore AI applications—commonly referred to in Silicon Valley as "forward-deployed engineers." Their primary role is to work collaboratively with clients to deploy AI tools effectively. Data from Indeed revealed that job postings for this position surged over 5,000% year-on-year in April.

Kopp expects the demand for such talent to continue escalating, particularly for individuals skilled in managing large data sets, working with AI, and designing agents, as consulting firms embrace more transformation initiatives. This trend aligns with a broader movement within the industry, as consulting firms increasingly recruit technical specialists to replace traditional entry-level roles impacted by AI automation.

Moreover, Kopp regards the AI shift as a valuable asset in attracting new talent. 

"A new wave is emerging. It's worthwhile to consider a career in consulting," he remarked. "This shift can serve as a beacon for the younger generation who are more technologically inclined to join these firms."

Rillet's CEO states that AI is altering the hiring practices of consulting firms.

A sunlit consulting firm boardroom with a large frosted-glass wall bearing the unicorn-shaped Rillet logo. At the polished wood table stand two piles: one of fading paper resumes dusting away, the other a neat row of digital tablets glowing with AI-generated candidate profiles. Rillet’s CEO stands at the head of the table, hands confidently on hips, as intrigued recruiters lean forward under warm natural light—capturing AI’s new role in shaping who consulting firms hire.

The CEO of the unicorn AI accounting startup, Rillet, says AI is changing who consulting firms hire - Business Insider

- Rillet aims to revolutionize accounting with AI, speeding up bookkeeping processes significantly.  
- The company has raised $100 million and is valued at $1 billion, attracting diverse clients.  
- Demand for specialized talent in consulting grows as AI automates traditional bookkeeping tasks.

For years, upgrading the software companies use for bookkeeping consumed a consultant's entire job.

"It's no fun being a consultant implementing your third instance of Oracle Fusion and having three years of your life basically go by in a blink of an eye because you're transforming Excel spreadsheets and trying to wrangle a very old system," Nicolas Kopp, CEO of AI-native accounting startup Rillet, told Business Insider.

Oracle Fusion is a suite of cloud software that large companies use to manage their finances and operations. Setting up systems like this can take years of consulting work. Rillet is betting AI can make that process faster by keeping a company's books up to date as transactions come in.

Its "objective function" is simple, Kopp said: "To reduce the time spent that humans go around clicking buttons in applications."

Rillet's growth also offers a glimpse of how AI could reshape consulting talent. As the software takes on more routine accounting work, firms are looking for people with deeper domain knowledge and the technical skills to work with AI and large data sets.

Related video How AI takes a toll on the freelancers who train, test, and refine it

The company, which emerged from stealth two years ago, said last week that it raised a $100 million Series C at a $1 billion valuation.

It's at the forefront of a growing crop of startups taking aim at the decades-old ERP market, and with more than $200 million in total funding, it is one of the most-funded companies building an AI-native alternative to legacy finance software.

The company now serves more than 600 public and private customers, including Mercor, Neuralink, Temporal, and Skild AI, and says 40% of its customer base is outside tech and AI in sectors like healthcare, financial services, retail, and biotech. It has captured half of its customers from legacy ERP systems, including NetSuite, Workday, Oracle Fusion, and Sage Intacct, while the other half comes from Intuit, according to the company.

The post-clicking future

AI-native startups like Rillet are turning the monthly ritual of closing the books into something similar to a normal workday.

In an Andreessen Horowitz analysis of 56 Rillet customers, 87% had fewer than 1% of their bookkeeping entries left to review when the end of the month rolled around.

The shift is part of a broader shake-up taking place across enterprise software. Investors have dubbed the recent sell-off in traditional software companies the "SaaSpocalypse," as advances in AI raise questions about whether businesses will continue paying for large numbers of software seats or whether newer AI-native products can replace them.

Kopp said he expects the way companies buy software to change. Charging customers based largely on how many employees use a product, he said, is likely to become "a thing of the past" as more work is performed by AI agents rather than people clicking through software themselves.

More engineers, more talent

If AI changes how enterprise software is used, then it also changes the kinds of workers consulting firms need to deploy and manage it.

In April, Rillet announced a "corporate development alliance" with EY. It now also works with several consulting firms, including RSM and KPMG, Kopp said.

In the near term, he believes the biggest opportunity for consulting firms is in "change management and implementation." The longer-term opportunity is to turn their decades of accumulated accounting expertise into "skill files, repositories, agents" that can be layered onto AI systems like Rillet.

"I think building agents is a huge opportunity," Kopp said. He added that Rillet is already helping a consulting firm build analytics and reporting agents for forecasting dashboards, as well as tools for controls and risk monitoring that make it easier to review large data sets rather than relying on manual testing.

That shift is changing the human talent they need, especially as the accounting profession continues to grapple with a yearslong talent shortage.

"Number one, the bar is going up," Kopp said. "AI is a great leveler of information. So you need very highly skilled accountants and accounting professionals at these firms. Otherwise, the AI can kind of do your job." Kopp also believes that "generalist" entry-level work will increasingly be absorbed by AI in the coming two to three years and create more demand for domain-specific experts.

At the same time, there's a new class of workers who are tech-savvy, innovative, and eager to experiment with AI — the kind Silicon Valley calls "forward-deployed engineers." They are essentially tasked with working directly with customers to help put AI tools to use. Job postings for the role were up more than 5,000% year over year in April, according to data from Indeed.

Kopp expects demand to keep rising for these types of workers, especially those who can handle large data sets, work with AI, and build agents as consulting firms take on more transformation projects. That's already consistent with a broader shift in the industry: Consulting firms are hiring more technical specialists as AI automates more traditional junior work.

He also sees the AI shift as a recruiting tool in its own right.

"There's a new wave coming. It's worth your time to go into consulting," he said. "They use this a little bit as a lighthouse, I think, for the younger generation, the people that are more tech forward, to come join their firms."

The CEO of the unicorn AI accounting startup, Rillet, says AI is changing who consulting firms hire

In what could be a transformative deal, Anthropic is set to acquire Israeli AI startup Decart for an estimated $7 billion. This acquisition could turn out to be exceptionally profitable for Decart's founders and investors once Anthropic proceeds with its anticipated IPO, which insiders speculate could take place as early as late August.

Interestingly, Anthropic plans to utilize shares as the primary form of payment, rather than cash, keeping Decart's shareholders invested in Anthropic's future value post-acquisition.

This could yield significant rewards considering Anthropic's swift rise in valuation. Just this year, it was valued at $380 billion in February and soared to $965 billion by May, following a substantial $65 billion funding round. Its annual revenue run rate by the end of July hit $65 billion, a notable increase from $47 billion in May and about $9 billion at the close of 2025.

With the upcoming IPO, Anthropic is eyeing a public offering that might match or surpass SpaceX's record-breaking $75 billion IPO. Should Anthropic go public at a valuation higher than what is suggested by the Decart acquisition deal, the shares allocated to Decart's investors could see a considerable increase in value. Conversely, a lackluster IPO could result in diminished financial returns for them.

This unique structure differentiates the Decart acquisition from traditional cash buyouts. Instead of simply cashing out with a fixed $7 billion, the founders and investors are essentially retaining a stake in Anthropic’s future growth trajectory.

Additionally, this deal will bolster Anthropic's presence in Israel, a hub for AI innovation. Decart specializes in enhancing AI efficiency with real-time applications, allowing Anthropic to tap into both its advanced technology and skilled team.

Founded in 2023, Decart boasts a workforce of around 100 employees and has successfully raised $450 million to date.

To navigate this strategic transaction, Decart has engaged boutique investment bank Catalyst as their advisor.

Decart's $7 billion Anthropic agreement may increase in value post-IPO.

A modern boardroom bathed in warm morning light, two silhouetted executives shake hands across a sleek glass table. Behind them, a large wall screen shows a bullish IPO graph soaring upward with “$7 B” and the Anthropic logo beside the rising curve. Decart’s logo is emblazoned prominently on a frosted glass wall in the background, sunlight glinting off its edges.

Decart’s $7 billion Anthropic deal could become far more valuable after the IPO - calcalistech.com

- Anthropic plans to acquire Israeli AI startup Decart for $7 billion, primarily in shares.  
- Decart shareholders' returns depend on Anthropic's IPO valuation, potentially increasing or decreasing payouts.  
- The acquisition bolsters Anthropic's presence in Israel, enhancing its AI technology and talent access.  

The reported $7 billion acquisition of Israeli AI startup Decart by Anthropic could become significantly more lucrative for its founders and investors when the Claude developer follows through with a blockbuster IPO.

Anthropic is expected to pay most of the consideration in shares rather than cash, meaning Decart shareholders will remain exposed to the value of Anthropic after the acquisition closes.

That could prove particularly valuable given how quickly Anthropic's valuation has risen. The company was valued at $380 billion in February and $965 billion in May, when it raised $65 billion. Its annual revenue run rate reached $65 billion by the end of July, up from $47 billion in May and roughly $9 billion at the end of 2025.

1 View gallery Anthropic Claude. ( Photo: Shutterstock )

Now Anthropic is preparing for a potential public offering that could come as soon as the end of August. Bloomberg reported that the company is considering an IPO that could match or exceed SpaceX's record $75 billion offering.

If Anthropic goes public at a valuation above the level implied by the Decart acquisition, the shares received by Decart's shareholders could appreciate significantly. The opposite is also true: a weaker IPO would reduce their potential payout.

The structure makes the Decart transaction different from a conventional cash acquisition. Rather than simply locking in a $7 billion exit, its founders and investors are effectively retaining a stake in Anthropic's next stage of growth.

The deal would also give Anthropic a major foothold in Israel. Decart has developed technology focused on AI efficiency and real-time applications, while Anthropic would gain both its technology and a team in one of the country's largest AI talent hubs.

Founded in 2023, Decart employs approximately 100 people and has raised $450 million to date.

Decart has hired boutique investment bank Catalyst to advise on the transaction.

Decart’s $7 billion Anthropic deal could become far more valuable after the IPO

In a move to broaden its educational offerings, Harvard Business School is incorporating artificial intelligence avatars to deliver personalized feedback to its students.

These innovative avatars have been developed by a startup known as HeyGen and are integrated into the HBS Foundry bootcamp, an eight-week program priced at $699, designed specifically for aspiring entrepreneurs. Although participants enjoy live weekly sessions with instructors, it is the AI avatars that step in to provide evaluations during practice pitches and board meetings.

New York Times reporter Sarah Kessler experienced this firsthand, pitching an AI-driven recreation of Jeff Bussgang, co-founder of Flybridge Capital. While both Bussgang and his digital counterpart were not particularly taken with her idea of creating “Uber for bananas,” Kessler noted that the avatar maintained a eerily static smile throughout her presentation.

Katharina Rings, the project director, initially thought of the AI feature as a simple chatbot. However, following feedback from a trial run, students expressed a desire for a more interactive experience.

Interestingly, while many college students have voiced skepticism about artificial intelligence, those in the Foundry program indicated their appreciation for the avatars. Bussgang himself remarked that while his digital doppelgänger may come across as somewhat “creepy,” he noted, “My students love it.”

Harvard's $699 startup bootcamp features AI avatars of its teachers.

A sunlit, airy Harvard startup bootcamp studio: adult entrepreneurs sit at sleek desks with open laptops, taking notes as lifelike AI avatars of instructors appear on slim desk-mounted screens, gesturing over digital whiteboards. A large Harvard crest hangs on the bright front wall, warm natural light flooding the room to evoke innovation and tradition united.

Harvard’s $699 startup bootcamp offers AI avatars of its instructors - TechCrunch

- Harvard Business School uses AI avatars for feedback in its entrepreneurial bootcamp.  
- Participants found the AI avatars more engaging than traditional chatbot interactions.  
- Despite mixed feelings, students appreciate the virtual avatars' role in practice sessions.  

In Brief

As Harvard Business School seeks to expand its reach, it’s leaning on AI avatars to provide individual feedback.

These avatars were created by a startup called HeyGen and are included in the eight-week, $699 HBS Foundry bootcamp for entrepreneurs. The program offers live sessions with instructors every week, but the AI avatars are the ones providing feedback during practice pitches and board meetings.

New York Times reporter Sarah Kessler actually tried this out herself by pitching an AI-generated copy of Flybridge Capital co-founder Jeff Bussgang. Apparently, both the real Bussgang and his simulacra were unimpressed by her plan to build “Uber for bananas,” but Kessler said the virtual version offered a noticeably frozen smile during her pitch.

Project director Katharina Rings said she initially envisioned the AI component as something closer to a chatbot. However, after HBS released a trial version, students said they wanted a more guided experience.

And while some college students haven’t been shy about expressing their negative feelings towards AI, Foundry participants told Kessler they like the avatars. As for Bussgang, he acknowledged his digital copy is a little “creepy,” but he said, “My students love it.”

Harvard’s $699 startup bootcamp offers AI avatars of its instructors

Michael Polansky is remarkably unassuming for someone operating in a corner of the world known for outsize egos.

Seated at a leafy patio outside a popular bakery in Mill Valley, an affluent town about 15 miles north of San Francisco, Polansky — bespectacled, his fresh face framed by dark hair shot through with gray — has the look and the friendly demeanor of a young professor.

He is, in fact, both the founder of a buzzy AI and biology startup called Outer Biosciences and the creative, business, and romantic partner to Stefani Germanotta — better known as Lady Gaga. It’s an unlikely double life. On the one hand, the couple invariably moves in the world that comes with celebrity; on the other, he’s running an outfit that has spent years figuring out how to keep living human tissue alive outside the body — for over a month, so far — without anyone outside the company knowing.

He didn’t see any of it coming. Polansky grew up in Minnesota and went on to Harvard, where he studied applied mathematics and computer science, graduating in 2006. Afterward, he logged three years at the hedge fund Bridgewater Associates — “a very unique place,” Polansky says over coffee, and one where he had “a really good experience,” even if it wasn’t a place he was going to “wake up and be excited about . . .every day.”

His pilgrimage from Bridgewater to Silicon Valley ran through Minnesota. By coincidence, Sean Parker’s assistant at the time had been Polansky’s neighbor growing up. At a 2007 wedding in their home state, she mentioned that Parker was looking for someone to work with him. Polansky already knew who Parker was and was looking to move west. The two had dinner in New York, “hit it off immediately,” and, as Polansky tells it, he quit Bridgewater the next day and moved to San Francisco.

He first landed a role as a principal at Founders Fund when the firm was run by its four original partners — Peter Thiel, Sean Parker, Luke Nosek and Ken Howery – with Polansky and another young principal at the time, Brian Singerman, sharing an office. “It was a really, really great experience,” Polansky says.

When Parker left Founders Fund after becoming liquid in his Facebook stock and wanted to build out his own family office, he brought Polansky with him. Polansky ran that office — handling Parker’s business, investment, and philanthropic interests, including helping stand up the Parker Institute for Cancer Immunotherapy (where Polansky remains executive director) until COVID, when his life “moved in a different direction.”

That change had a lot to do with Germanotta. Polansky met her in late 2019 at one of Parker’s birthday parties. Charmingly, the meeting came at the urging of her mother, Cynthia Germanotta, president of the Born This Way Foundation, whom Polansky had come to know through his philanthropic work.

“She had said, you know, for months and months, ‘I want to set you up with my daughter,’” Polansky recalls. “I was like, I think you’re making fun of me.” She wasn’t. When their own mothers later met, he says, laughing, “it all made perfect sense.” (His mother and Germanotta’s mother are now close friends.)

Their relationship is a full partnership, professionally and personally. Notably, for Gaga’s most recent world tour, which began in July of last year and ended in April, the couple managed a massive operation across three 747s, something Polansky compares to running “a 200-person startup that travels around the world every day.”

It also includes Haus Labs, the cosmetics brand Germanotta initially built “on her kitchen floor,” Polansky says, instead of simply licensing her name to an existing company. That business, based in El Segundo, California, an operation with roughly 70 employees, is reportedly thriving.

Germanotta also sits on the board of Outer Biosciences, and the two companies collaborate at the margins. For example, Outer Biosciences’ chief scientist, Kyung-Jin Jang, sits on Haus Labs’ scientific advisory board, and the companies have run some joint projects.

Says Polansky, beaming as he talks about her from our sun-dappled table: “People really haven’t gotten to know a certain side of her publicly … She’s such a brilliant businessperson.”

From cancer to tissue in a dish

While Polansky is also a businessperson, he’s not a scientist. He got into life sciences “accidentally,” he says, through more than a decade spent alongside Parker in cancer immunotherapy, a field that was “very fringe” when they entered it.

Outer Biosciences, which Polansky founded in 2022 and where he is CEO, grew out of frustration that the pace of innovation in biology and chemistry has never matched software, in large part because there’s no ethical way to run experiments directly on people. Meanwhile, the proxies scientists rely on instead — animal models, simplified cell cultures, lab-grown organoids — are poor stand-ins for how a real human organ behaves.

So Outer Biosciences took a different approach. Instead of engineering a synthetic organ, the company sources human skin that would otherwise be discarded after surgery – mostly plastic surgery – through what it describes as vetted non-profit and commercial biobanks and brokers operating under “institutional review board oversight and documented donor consent,” principally the National Disease Research Interchange and the Cooperative Human Tissue Network. (Both outfits receive federal funding from the NIH and the National Cancer Institute without being federally operated.)

Polansky is careful to note that there is no single government tissue network that qualifies buyers. He says Outer Biosciences pays fees to these suppliers on a cost-recovery basis rather than purchasing tissue outright. He also says the company spent roughly two years on building that pipeline and handling the protocols required to receive that tissue “within hours” of surgery, while it’s still living.

Asked about the donors’ privacy, he says that every sample arrives already de-identified — stripped upstream by the supplying organizations of names, contact information and other direct identifiers. A proprietary support system developed by his team then feeds the tissue nutrients and removes metabolic waste, extending its viable life well past the industry norm.

That norm, by the way, is a matter of days. That’s enough time to test for acute toxicity, but not for slower biological processes like collagen remodeling, pigmentation change, or barrier repair that take weeks to unfold. (Dermatologists routinely tell patients to expect changes over a matter of weeks for this same reason.)

Outer Biosciences’ system meanwhile keeps tissue alive for up to a month, says Polansky, who says it retains its “day-zero architecture and preserves its day-zero epidermal, stromal and immune-associated molecular programs.” In plainer English, that means that 30-day-old tissue cared for by the company looks a lot like day-one tissue, but it isn’t fully indistinguishable from it.

Sunburn is one of the clearer examples of what that extra time buys Outer Biosciences. Polansky says that its researchers can induce UVB damage in living tissue, then track the stress, inflammatory, and recovery-related responses that follow over the following weeks as an information-gathering exercise. He says the team isn’t “healing” the skin but rather watching an injury happen and then watching the biology that follows it over time.

Perhaps anticipating pushback from the scientific community, Polansky is careful about how he frames the company’s achievements when this reporter asks questions about rival technologies. The startup’s value, he says, isn’t any one piece of what it’s doing but how the pieces fit together: human tissue that can be kept alive for weeks, a diverse donor pool that Outer Biosciences’ team can subject to controlled experimental conditions, and repeated molecular measurements taken along the way.

And it’s all fed into one, closed self-enforcing system. An AI model predicts which untested chemicals are likely to have a beneficial effect on a specific skin function. Those chemicals get run through the living-tissue system. Then the results, whether the prediction was right or wrong, get fed back into the model, improving the next round of guesses.

It’s a giant improvement from where things started, says Polansky. Early on, the company relied on a “brute force” approach, mining scientific literature and partnering with the National Cancer Institute on natural compounds from extreme environments. That phase produced a couple of leads over about 18 months, but with AI layered in, the company is now generating a new candidate roughly every six weeks, with six leads currently active in its pipeline and several dozen additional “hits” logged.

What makes that pace truly astonishing, Polansky says as the crowd around us thins out, is the size of the current universe of skin-active ingredients.

It’s almost impossible to know the exact number, but it’s small. “Active ingredient” means something different informally than it does formally. While the FDA maintains rules covering 13 categories of over-the-counter skin drugs (think sunscreen, antifungals), across all of them, only about 120 to 130 active ingredients are approved. Add cosmetic ingredients backed by actual research, says Polansky, and that number is closer to 200.

This, of course, presents opportunities.

Outer Biosciences is discovering cosmetic ingredients, not drugs, so there’s no FDA approval to seek out. Instead, the route runs through two steps: first, getting the ingredient a standardized industry name; then safety testing under guidelines set by the OECD, a Paris-based international body whose member countries agree to accept each other’s properly run studies — meaning a study done correctly in one participating country is accepted in the other 40-plus.

A partner outfit then commercializes the whole thing. Indeed, rather than build its own consumer brand, Outer Biosciences right now plans to license or sell its finished ingredients to beauty or pharma outfits that will then formulate these into actual products (a serum, a cream) and bring them to market under their own brands. Already, four of Outer Biosciences’ six current leads look likely to reach commercialization, Polansky says.

In the meantime, the company is generating money from collaborative research partnerships, including a pharmaceutical partner that’s studying why certain cancer drugs cause severe skin rashes, and consumer beauty brands that are testing whether Outer Biosciences’ data holds up against their own product-development and marketing needs.

If Polansky is raising more money for the company currently, he won’t say. To date, the company has raised roughly $23 million, with early backers including Wing Ventures, Initialized, and Polansky’s own investing firm, Hawktail, among others. The company employs 19 people, with all but Polansky based just outside Cambridge, Massachusetts.

Asked why he’s chosen now to talk about the company after years of near-total silence — he says he barely discussed it even with close friends — Polansky points to the data the team is beginning to amass and the confidence that has given them. “Trying to do this in private is hard,” he says, as the wait staff start flipping chairs onto tabletops, signaling it’s closing time at the bakery. “We kind of want to start working in public now,” he adds, shrugging.

Outer Biosciences is not the only company chasing this idea, even if its use of real tissue, rather than synthetic, is distinctive.

Vivodyne — a Philadelphia-based competitor building lab-grown human organ tissue paired with predictive AI to replace animal drug testing — just this month announced it has raised close to $80 million to date, including a $38 million seed round and a $40 million Series A, both led by Khosla Ventures.

Other rivals are pursuing various flavors of organ-on-a-chip and microphysiological systems for preclinical testing.

Polansky doesn’t seem especially preoccupied with any of them — less, it seems, out of arrogance than because he seems to have his hands full. Besides, there’s plenty of room for everyone in this moment. Unlike AI companies training on scraping the internet, there is no “biology internet” to scrape.

And Outer Biosciences has two other reasons to focus on its own knitting. First, the data it generates doesn’t exist anywhere else, which, conceivably, makes the company’s position more defensible, if a lot slower, to build than “traditional” software-based AI startups. It’s also cheaper to run, with modest compute demands compared with training a large language model. In fact, all of the company’s AI work currently runs on-premise, not in the cloud, because “we don’t want the data in the cloud,” Polansky says.

Whether over time, Outer Biosciences becomes a standalone commercial-ingredients business, licenses its discoveries, or eventually reorganizes around a single breakout compound, Polansky says he hasn’t settled on – and the team doesn’t need to. The more important goal, he says, is a predictive model that’s accurate enough that the company can spot promising directions in skin biology without having to run every experiment physically first, opening up a rate of discovery in dermatology that doesn’t currently exist.

For now, instead, the work of turning a promising compound into a real product — the formulation, the manufacturing scale-up, the supply chain, the safety testing — is still done manually by the same scientists who discover the compounds in the first place. Building out a product-development team, with people who’ve done this kind of work before, is next on the roadmap.

“I think it’s going to be fun,” he says, “to have people know that this is what we’ve been doing.”

Michael Polansky is training an AI model on skin that’s still alive

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Michael Polansky is training an AI model on skin that’s still alive - TechCrunch

Rillet co-founder and CEO Nicolas Kopp seems justifiably confident as we talk over Zoom a day after his company announced a $100 million raise at a $1 billion valuation. The U.S. has a shortage of accountants right now, which is driving growth of his AI-native accounting platform so much, he raised that cash in 48 hours without even trying.

Rillet emerged from stealth two years ago. Since then, it has raised $200 million from top investors like Iconiq, Andreessen Horowitz, and Sequoia. It’s also amassed 600 customers, most of whom are looking to ditch legacy accounting systems like Oracle and NetSuite, Kopp says.

A few weeks ago, Rillet held a board meeting and shared with investors its growth since its $70 million Series B last summer. Annualized revenue rate had doubled in the last quarter alone; the startup added new clients, many of them public companies, and an alliance with EY to introduce AI tools to the auditing giant.

His customers aren’t piloting Rillet either, he said — they’re yanking out ERP and accounting software from competitors like Intuit, NetSuite, or Oracle.

After that board meeting, text messages were fired, calls were made, and 48 hours later, Rillet was a unicorn. The company wasn’t even looking to raise, Kopp said.

Seth Pierrepont, the general partner at Iconiq who led the round, said that the deal came together fast but “it wasn’t a cold start,” he described.



“Rillet had already proven it could win against the incumbents that have owned this category for decades,” Pierrepont told TechCrunch. Iconiq also co-led the company’s Series B, and with this latest round, Pierrepont joins the Rillet board. “A year of watching the team deliver on that made doubling down and leading the Series C an easy call.”

Julien Bek, Sequoia’s lead investor on the deal, also said that, though 48 hours might look rushed from the outside, from their perspective, re-investing in Rillet was a “very easy decision,” after the company’s growth in the past year.

“Rillet’s initial wedge is accounting, but ultimately they are reinventing the entire finance function,” Bek told TechCrunch, adding that agentic finance could become “one of the largest application software opportunities of the AI era.” Sequoia led Rillet’s Series A last summer.

“When the opportunity came together,” Bek continued. “We already had all the context we needed.”

Rillet is one of many AI-native startups now giving legacy players a run for relevance. Earlier this year, software stocks on the public market dipped as investors worried about how emerging AI tools would affect them. Kopp thinks there’s some truth to that.

“AI is going to come hard at these legacy players,” he said, because it is giving customers compelling alternatives.

Rillet, for example, was built for AI agents, not humans, letting humans work alongside the AI agents on corporate bookkeeping. Rillet clients range from laundromats to a major sports franchise. Some 50% of Rillet customers come from Intuit, 30% from NetSuite and Sage Intacct, and 20% from Oracle, SAP, Workday, and Microsoft products, he said.

Security is critical when working with sensitive client data, Kopp said. Rillet includes model routing, so customers can redirect requests to the foundational model of their choice (like OpenAI or Anthropic), and Rillet’s harness prevents these models from training on their data, he says.

Rillet product imagery Image Credits:Rillet

There’s also no cross-training — meaning one customer’s data remains proprietary. The agents also have memory, so they can remember and store historical actions they can then use for their own process and improvement.

About three months ago, Rillet released a governance feature letting accountants see and audit every decision the AI agent has made — including what numbers the agents pull and how they calculated them. Creating this was harder than it looks, Kopp said, because the team had to compress agent data into a format humans could understand.

Kopp said this feature was only possible to build recently because AI agents have gotten so powerful so quickly. They can, for example, now support multi-step workflows over longer periods of time. Because of that, auditing what they are doing has become even more important for clients.

“We barely scratched the surface of potential and opportunity that this technology has,” he said.

Right now, regulations for public companies require that every transaction made by an AI agent be approved by another human. He thinks regulators and top names are watching how the accounting industry evolves around this new technology. He’s hopeful that new rules and regulations will evolve that align more with where everything is headed.

“It’s a very normal process,” he said. “Similar to when the cloud came, of just getting everybody familiar with what’s going on and how it helps the profession.”

Kopp also doesn’t think mass job displacement from AI is coming anytime soon, especially in accounting. (Stanford released a report a few weeks ago that found no widespread job displacement yet.) He insists that Rillet isn’t a human replacement, not even for junior accountants. They can use Rillet to help automate and assist with some of the profession’s grunt work.

He also pointed out the expected shortage of accountants in the U.S. The number of those graduating with an accounting degree has been declining since at least 2010. In a recent report, the Controllers Council Organization found that 61% of finance leaders have struggled to find finance, accounting, and CPA talent in the past year. The pullback is not entirely shocking: accountants’ hours are long, the pipeline to the top is arduous, the pay often doesn’t match the workload, and the work doesn’t appeal to everyone.

At the same time, the Bureau of Labor Statistics has projected that accounting-related needs are expected to grow by at least 5%, adding 72,800 jobs by 2034. It also doesn’t expect AI to reduce the demand for accountants, even as the technology becomes more widespread. “The automation of routine tasks, such as data entry, will instead make accountants’ advisory and analytical duties more prominent,” the BLS said.

“I just don’t see people losing their job anytime soon,” Kopp said. “These people have started their professions to help businesses make better financial decisions,” he added. “We can fully enable them to do that.”

This piece was updated.

How AI accounting startup Rillet raised $100M and became a unicorn in 48 hours

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How AI accounting startup Rillet raised $100M and became a unicorn in 48 hours - TechCrunch

The near-bottomless demand for unique AI training data from top labs and corporations is driving a massive boom for a cohort of data-labeling startups.

One of these fast-growing businesses is Micro1, a four-year-old startup that expanded its gross annual run rate from $100 million to $500 million over the past eight months, according to a person familiar with the company. Like its peers that hire domain experts such as doctors, lawyers, and scientists on a contract basis, Micro1 retains roughly 60% to 70% of that figure, putting its net annual run rate between $150 million and $200 million.

While Micro1 still lags competitors like Mercor (which hit $2 billion in gross annualized revenue this summer) and Handshake (which reached $1 billion earlier this year), the startup’s revenue growth shows that there is more than enough demand to support multiple players supplying AI training data.

The rapid growth is bound to continue, with some researchers hypothesizing that future AI spending on data could rival spending on compute.

That outlook bodes well for Micro1, which is seeing its contract sizes grow at an accelerated pace and expects its margins to expand over time. The startup is increasingly generating synthetic data without human involvement, such as by creating automated descriptions of video content. Additionally, some of the data it generates can be sold to multiple customers, driving gross margins for this “off-the-shelf” data as high as 80% to 90%, a person familiar with the startup’s finances told TechCrunch.

Selling the same datasets to multiple clients has sparked recent controversy, with critics arguing that distributing off-the-shelf data to Chinese AI developers helps make their models as powerful as top U.S. models.

Micro1’s founder, Ali Ansari, said last month on X that unlike some of its competitors, the startup doesn’t sell its data to Chinese model makers. “Some human data companies work with foreign adversaries. [A]nd the results show today in Kimi K3. We believe it’s shameful to claim American AI dominance desires while selling millions worth of data to countries that we are in adversarial competition with.”

Like Mercor, Micro1 began as an AI recruiting startup. But after noticing that data-labeling clients were using his AI platform to vet and recruit engineers for annotation, Ansari decided to pivot and enter the data-labeling business, too.

Ansari previously told TechCrunch that in addition to having its experts evaluate model outputs — a concept known as reinforcement learning gyms — the company is building a robotics pre-training dataset by having hundreds of generalists record everyday object interactions in their homes.

Micro1 raised its Series A at a $500 million valuation last September, and TechCrunch understands that the startup may have recently raised another round at a significantly higher valuation.

Micro1 didn’t respond to a request for comment.

AI data startup Micro1 reaches $500M gross run rate amid AI training boom

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AI data startup Micro1 reaches $500M gross run rate amid AI training boom - TechCrunch

A new player in the AI landscape is vying for access to Spirit Airlines' data. Ali Ansari, the 25-year-old founder and CEO of Micro1, a startup focused on enhancing AI model training, revealed to Business Insider that his company has proposed a significantly higher bid for Spirit's data, following Google’s successful $10 million offer.

On Wednesday, Micro1 formally submitted a $12.5 million bid to Spirit Airlines' legal representatives, as confirmed by a source familiar with the development. As part of its bankruptcy proceedings after filing last year, Spirit Airlines is liquidating its assets, which includes valuable corporate data.

Experts in bankruptcy proceedings stated that while it's atypical for courts to entertain late submissions such as Micro1's, it is not entirely outside the realm of possibility, especially if the new offer can provide greater financial returns for creditors.

Ansari emphasized the importance of company data in training AI systems, noting its potential for enhancing model performance with more realistic training inputs. He characterized Google's offer as "actually quite low" considering Spirit Airlines' extensive operational history, adding that Micro1 compensates other data providers up to $2 million for their information.

Operating out of San Francisco, Micro1 employs gig workers to refine AI models for its clientele and has created digital environments where AI agents can master tasks, such as booking travel tickets. Founded in 2022, the startup boasts around 150 employees and has sought valuation offers of up to $2.5 billion, as noted by Forbes last December.

The competition for Spirit Airlines' data isn't limited to Micro1; another AI training company, Mercor, previously entered the fray, resulting in a bidding contest that saw Google’s initial bid of $5 million escalate to $10 million. Mercor ultimately placed a final bid of $7.5 million but fell short against Google's offer.

Neither Google, Spirit Airlines, nor Mercor have commented on Micro1's recent bid. The creditors’ committee for Spirit Airlines also did not respond to inquiries regarding the matter.

The potential for Micro1 to disrupt Google's agreement remains uncertain. Legal analysts suggest that bankruptcy judges sometimes consider later bids if they promise greater returns for creditors but stress that maintaining the auction process's integrity is crucial.

"A well-publicized and organized auction is typically not overturned," stated Nancy Rapoport, a bankruptcy law professor at the University of Nevada, Las Vegas, adding that the initial higher bidder was given the chance to participate in the auction. Meanwhile, Lindsey Simon, an associate law professor at Emory University, mentioned that the final decision often depends on the presiding judge.

As of now, the federal bankruptcy court in New York has yet to ratify the auction results. A hearing regarding the data sale has been scheduled for September 9, and Ansari indicated that Micro1 is preparing to provide comprehensive details about its offer to the court.

AI startup Micro1 plans to contest Google's successful bid for Spirit Airlines data by submitting a higher proposal.

A sunlit corporate auction suite with floor-to-ceiling windows overlooking a Spirit Airlines jet on the tarmac, its logo bold on the tail. On a polished mahogany table sit two oversized illuminated bid paddles: one bearing Google’s logo, now dimmed, and beside it a brighter paddle stamped with the Micro1 logo—capturing the tense David-versus-Goliath moment of a higher offer.

AI startup Micro1 wants to challenge Google's winning bid for Spirit Airlines data with a higher offer - Business Insider

- Micro1 offered $12.5 million for Spirit Airlines' data, surpassing Google's $10 million bid.  
- Spirit Airlines is selling data as part of its bankruptcy proceedings from last year.  
- Bankruptcy court may consider late bids if they benefit creditors or shareholders significantly.  

Another AI company wants to get its hands on Spirit Airlines' data.

Ali Ansari, 25, the founder and CEO of Micro1, a startup that helps train AI models, told Business Insider that his firm is making a "materially higher" offer for Spirit Airlines' data after Google successfully bid $10 million for it this week.

Micro1 sent a $12.5 million offer to Spirit Airlines' legal team on Wednesday, a person familiar with the matter said.

Spirit Airlines is selling off its assets in bankruptcy court — including troves of corporate data — after going under last year.

Bankruptcy experts told Business Insider it would be unusual — but not out of the question — for the court to consider Micro1's offer after it missed the deadline to bid in the original auction.

Related video Microsoft is betting big on AI. Company insiders have serious doubts.

Ansari said Micro1's interest reflects the value of company data for training AI models, as it contains the kind of messy inputs that help AI models learn to operate in real-world environments.

"Realistic data is very valuable," he said, calling Google's winning bid "actually quite low" given Spirit Airlines' decades of operation. Micro1 pays other companies up to $2 million for their data.

Based in San Francisco, Micro1 pays gig workers to improve AI models for its clients, and runs digital 'environments' where AI agents can get better at tasks like booking train tickets. Founded in 2022, it has about 150 employees and has fielded offers at a $2.5 billion valuation, Forbes reported in December.

Micro1 CEO Ali Ansari. Micro1

AI training startups are scrambling to acquire data from companies to supercharge their clients' chatbots. Mercor, another AI training startup, also bid for the Spirit Airlines data, sparking a bidding war with Google, which initially bit $5 million. Mercor's final bid of $7.5 million lost to Google's $10 million.

Google, Spirit Airlines, and Mercor declined to comment on Micro1's last-minute move. A representative for Spirit Airlines' creditors committee didn't respond to requests for comment.

Whether Micro1 can actually disrupt Google's deal isn't clear.

Bankruptcy law professors told Business Insider that judges sometimes entertain late bids if they could generate significantly more money for creditors and shareholders, or offer other terms that those parties find more favorable.

At the same time, courts also want to preserve the integrity of the original auction process.

"A duly noticed, well-run auction generally won't get undone," Nancy Rapoport, a law professor at the University of Nevada, Las Vegas, said. "The higher bidder had the opportunity to bid during the auction."

Lindsey Simon, an associate law professor at Emory University, said it often comes down to the judge overseeing the case.

"The bankruptcy code isn't clear on this," she said.

The federal bankruptcy court in New York has not yet approved the auction results.

On Tuesday, it delayed a hearing on the auction after a group of former Spirit Airlines' flight attendants objected over concerns about what would happen to their data.

Google previously told Business Insider that any data it receives will be "rigorously scrubbed" of any personally identifiable information by a third party.

A hearing for the data sale will be held on September 9. Ansari said Micro1 is working on submitting details about its offer to the court.

AI startup Micro1 wants to challenge Google's winning bid for Spirit Airlines data with a higher offer

Andreessen Horowitz (a16z) has garnered attention for its American dynamism thesis, but holding a U.S. passport isn't essential for entrepreneurial success. Gabriel Vasquez, a partner specializing in AI applications and the firm's global investment strategy, highlighted that “44% of our investments in the Apps Fund One and Two feature founders from outside the U.S.”

Alongside general partner Angela Strange, Vasquez spearheads a16z’s Borderless Founder network, an initiative aimed at empowering immigrant and international entrepreneurs. The duo asserts that exceptional companies can emerge from anywhere, but they’ve come to believe that foreign founders may hold a competitive edge over their American counterparts.

Historically, the U.S. has been a magnet for international innovators, but a16z recognizes that the current landscape, particularly in the AI sector, favors those with connections in both their home countries and Silicon Valley. “There is now an advantage to having one foot in your home country and one foot in Silicon Valley,” Vasquez and Strange noted in a pre-release post shared with TechCrunch.

In a conversation with TechCrunch, Vasquez detailed how this emerging advantage has prompted a16z to expend “more than one million air miles” pursuing international investment opportunities, rather than simply waiting for teams to relocate to the U.S.

This shift didn’t happen in isolation. Especially for enterprise startups, previous patterns of international buyer engagement showed limited activity and a reluctance to spend. Vasquez pointed out that “buyers from countries outside the U.S. were not moving rapidly, and their willingness to pay was very low,” highlighting how the landscape has evolved.

Over the past three to five years, many startups have begun to secure substantial clients globally, even in markets that are typically less recognized for tech advancements.

When a16z began receiving interest from seed-stage startups collaborating with Fortune 500 companies across the globe, Vasquez initially suspected it might be an anomaly. However, he quickly realized it was a broader trend. Numerous international AI startups are now landing significant clients early in their development—an occurrence that was rare just a few years back.

In Europe, large corporations previously engaged with startups primarily through open innovation programs or accelerators, seldom committing significant funds. This made converting these startups into paying customers a considerable challenge, prompting France to launch initiatives like “I Choose French Tech.” Yet, according to Vasquez, AI has catalyzed a substantial shift in this paradigm.

AI technology has led established companies to understand the necessity of incorporating third-party solutions to stay competitive—even in regions like Latin America, where labor costs used to deter software development. “Software never really took off in the region due to the competition from cheap labor,” Vasquez explained. However, with the rise of AI agents that are more accurate and perpetually accessible, they have found a role in customer service and other fields.

The demand for AI solutions at the enterprise level is rapidly increasing worldwide, yet Vasquez noted that many American startups currently lack the agility to meet these needs from the outset, which often results in them prioritizing domestic clients instead.

This gap presents an opportunity for local founders to develop AI solutions for businesses in their home countries, while maintaining connections to the U.S. “The notion of headquarters is evolving; it’s becoming more flexible,” Vasquez remarked, observing that even governmental views are shifting in this direction.

A relevant example is Poland, which recently invested in a16z portfolio company ElevenLabs. Although the voice AI startup only maintains a subsidiary in Poland, it boasts clients like InPost and LOT Polish Airlines, and is co-founded by Polish entrepreneurs Piotr Dąbkowski and Mateusz Staniszewski—indicative of the strong presence of Polish talent in the AI sector, which is also notable at OpenAI.

Vasquez believes that access to talent serves as a crucial differentiator in today's market. “Recruiting in Silicon Valley is incredibly challenging since you’re up against companies like Anthropic and OpenAI, which have secured massive funding for top talent.” In contrast, international founders frequently tap into deep talent pools located outside the U.S.

These talent hubs are why Vasquez finds himself frequently traveling, often to Stockholm, to scout for the next potential unicorn. Some of Europe’s leading AI scaleups have emerged from academic institutions, catching the attention of venture capitalists. In this context, it’s worth noting the observation from Dealroom founder Yoram Wijngaarde: “European talent remains one of America’s biggest startup advantages.”

AI provides an edge to foreign founders, according to a16z.

A bright, sunlit startup incubator where a diverse group of adult founders lean over a glass table, collaborating on sleek laptops displaying AI-generated designs. Warm morning light streams through floor-to-ceiling windows. A large a16z logo banner hangs on the wall, and behind them a digital world map on a screen glows with network lines tracing global connections.

For a16z, AI gives foreign founders an advantage - TechCrunch

- A16z's Borderless Founder network supports international founders, reflecting a shift in investment focus.  
- The rise of AI has enhanced global startup engagement with major companies outside the U.S.  
- Recruiting talent locally is increasingly vital as competition in Silicon Valley intensifies.  

Andreessen Horowitz has made headlines for its American dynamism thesis, but a U.S. passport is no requirement. According to Gabriel Vasquez, a partner focusing on AI apps and the firm’s global investment strategy, “44% of our investments in the Apps Fund One and Two have an international founder.”

Together with general partner Angela Strange, Vasquez is the driving force behind a16z’s Borderless Founder network, an initiative to support immigrant and international founders. Their premise is that great companies could be born anywhere, but they now believe foreign entrepreneurs actually have an edge over their American peers.

The U.S. has always attracted foreign founders; but in the current AI-dominated cycle, a16z acknowledges that their roots are more helpful than they used to be. “There is now an advantage to having one foot in your home country, and one foot in Silicon Valley,” Strange and Vasquez wrote in a post to which TechCrunch had early access.

Talking to TechCrunch exclusively, Vasquez broke down how this advantage has become significant enough for a16z to “spend more than one million air miles” in order to go after international dealflow — rather than expecting each and every team to move to the U.S.

This expectation didn’t come out of nowhere, especially for enterprise startups, where there’s been a marked shift in buying patterns from those based outside the U.S. “The buyers from countries outside the U.S. were not moving rapidly, and their willingness to pay was very low,” Vasquez said of the old pattern.

But this has changed dramatically “in the last three to five years,” with startups now able to secure major companies worldwide as customers, even in less cutting-edge markets.

When a16z started hearing from international seed-stage startups working with Fortune 500 companies, “we thought this might be an exception, but it was clearly a trend,” Vasquez said. Examples now abound of international AI startups signing major clients early on — but Vasquez is also right that it was rarely the case even a few years ago.

In Europe, in particular, it used to be that corporations would only engage with startups through open innovation programs and accelerators, but rarely with their main checkbook. Turning them into paid customers was hard enough that France launched a dedicated initiative, “I Choose French Tech.” But according to Vasquez, AI has been the driver in making this shift a reality.

That’s because AI made legacy players realize they would have to buy third-party solutions to remain competitive — even in areas where human labor is still affordable, like Latin America, Vasquez said. “Software never really picked up in the region, because you were competing with cheap labor.” But now that AI agents are “always on” and increasingly accurate, they have become commonplace in customer service and more.

Others could go after these opportunities, too. “There’s so much appetite at the enterprise level for companies all around the world to consume AI, but American [startups] don’t have the speed yet to go serve the entire market from day zero, so they obviously prioritize U.S. companies,” Vasquez said.

This leaves the door open for a local founder to sell an AI solution to companies in their country, while splitting their time between home and the U.S. “The concept of headquarters is something that is changing a lot; it’s just more fluid,” Vasquez said, noting that even governments seem to take a similar view.

Case in point: Poland recently took a stake in a16z portfolio company ElevenLabs. The voice AI startup only has a subsidiary in the country, and not its headquarters, but its customers include InPost and LOT Polish Airlines, and its founders are Piotr Dąbkowski and Mateusz Staniszewski — two examples of Polish talent in AI, also strongly present at OpenAI.

From Vasquez’s point of view, access to talent is a key differentiator. “Right now, recruiting in Silicon Valley is the hardest thing, because you’re competing with Anthropic and OpenAI that have raised billions and billions of dollars for the best talent.” But international founders are often tapping into the talent pool that exists in many places outside of the U.S.

Talent clusters are also the reason why Vasquez has been spending a lot of time on a plane — often in Stockholm — in search of the next unicorn. Some of the top AI scaleups are European academic spinouts, and VCs are going after them. In a sense, the story goes the other way around; to quote Dealroom founder Yoram Wijngaarde: “European talent remains one of America’s biggest startup advantages.”

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