That creates enormous productivity potential, but it also creates a new security problem: Companies now need to protect not only users, devices and applications, but software actors that can take actions on their behalf.

AI agents are becoming a new class of enterprise identity

An agent may access corporate files, query databases, send emails or execute code. Once it has that level of access, it needs permissions, monitoring and governance. Companies will need to know which agent accessed what information, which systems it connected to, and whether the actions it took were authorized.

As enterprises move from experimenting with a few agents to deploying hundreds of them, agent identity will become another important layer of cybersecurity. The challenge is that these identities are not passive. Agents can move between systems, invoke tools and make decisions, which makes controlling them more complex than managing traditional users or service accounts.

The value will sit in specific control points

This market will probably not develop as one broad category called “AI security.” The real opportunity will be around specific control points.

One company may protect agent identity, another may control the data an agent can access, while others may focus on prompts, MCP servers, plug-ins, traffic or auditability.

We are already seeing activity around these areas. recently acquired Israeli startup which focuses on real-time data classification and policy enforcement. Israeli cybersecurity startup , meanwhile, raised a $27 million Series A led by and focuses on understanding and securing increasingly complex internet traffic, including traffic generated by autonomous systems.

These companies are solving different problems, but together they show how the market may begin to separate into distinct security layers.

These control points are creating a new M&A map

Identity providers may extend identity governance to autonomous agents. Data-security vendors may need to control what information agents can access. Cybersecurity platforms, cloud companies and enterprise software vendors may eventually need agent-security capabilities embedded directly into their products.

For entrepreneurs, this means that “AI security” may already be too broad a positioning. The more important question is what exactly the company controls.

is a strategic adviser to tech companies, investors, CEOs and boards, specializing in strategy, growth and M&A. He is a guest contributor to ���ϳԹ� News and a university lecturer on strategy, finance and entrepreneurship. Learn more at and connect with him on .

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led the San Francisco-based company’s Series A, with participation from , , and of . The financing brings Baselayer’s total funding to about $40 million since its 2023 inception, according to co-founder and CEO . The company declined to disclose its valuation.

Baselayer combines business identity, credit and fraud data to help banks, fintech companies and other financial-services providers evaluate prospective customers. It sells its products directly and through software companies that resell or put their own branding on Baselayer’s technology. Its automated platform initially focused on Know Your Business, or KYB, identity verification, fraud detection and risk management.

More than 2,000 financial institutions — representing over 20% of such institutions in the U.S. — use its technology to onboard, underwrite and open accounts for merchants, according to Awad. Baselayer also works with Fortune 500 companies and has about 50 employees across offices in San Francisco and New York. Since its founding, the startup claims it has helped customers prevent more than $1 billion in fraud losses.

Awad declined to reveal hard revenue figures, saying only that Baselayer reached eight figures in revenue in less than two years.

Now, Baselayer is using its new capital to address a newer — and growing — identity problem: determining whether an AI agent is actually authorized to act on behalf of a particular person or business.

With people using AI agents left and right these days to book a restaurant reservation, for example, it’s becoming increasingly challenging to determine whether an AI agent’s automated activity is legitimate or if it’s a bot attempting to scrape data or commit fraud.

Alongside its raise, Baselayer today is also announcing the launch of its Agentic Identity Suite, extending its identity network from businesses to the AI agents transacting on their behalf.

From businesses to the agents acting for them

Awad and co-founder started Baselayer in February 2023, initially focusing on the lengthy and fragmented process financial institutions use to verify businesses and assess risk.

“What we set out to do was essentially bring risk assessment to the 21st century,” Awad recalls.

Awad describes Baselayer as both an identity network and a fraud consortium. Because its technology is used across thousands of financial institutions, Baselayer says it can recognize when the same person or business applies at multiple institutions and incorporate that activity into its risk scoring.

The company processes tens of millions of applications and says it sees many of the same businesses multiple times a year. That data becomes more useful as additional institutions and reseller partners join its network, according to Awad.

“We’ve essentially streamlined 10 years’ worth of selling into two years,” he said.

An AI agent presents a different problem, however. It may be created for a single task and disappear immediately afterward, leaving little or no history for a bank or risk provider to evaluate.

“Agents spin up and they spin down,” Awad said. “How can you trust this random one-task agent?”

To address this dilemma, Baselayer is developing what it describes as “Know Your Agent,” or KYA. The system is being designed to do things such as determine not only who deployed an agent, but also who that agent represents and whether it actually has permission to carry out a particular task.

It wants to do this by providing an authorized agent with a credential it can present when attempting to make a purchase or interact with another business. Then, when presented with a credential, a merchant, financial institution or online platform could use that information to decide whether to allow the transaction to proceed, Awad explained.

The startup is working with agent developers, payment processors, merchants and fraud-detection providers to issue and recognize its credential. They include , and Socure, among others. Unless agents can establish that they are acting on behalf of legitimate people or businesses, “agents will just get blocked everywhere,” Awad said.

AI can also make fraud easier to scale

Ironically, the same technology that allows legitimate agents to do more tasks can also help fraudsters operate faster.

In the past, identity fraud involved someone getting their hands on stolen personal and business information, creating a credible-looking identity, and then repeatedly applying for bank or credit card accounts until an institution approved one. At one point, the process took significant time and manual work. But today, AI agents can automate parts of it and run continuously.

“It’s fraud on steroids right now,” Awad said. “It’s so easy, it’s so cheap, it’s so fast, and it’s 24/7.”

Reports of AI agents bypassing restrictions have also raised questions about how to identify and control autonomous software. , for example, recently reported incidents in which its models took unauthorized or deceptive actions, including activity involving the e platform.

Baselayer’s technology would not keep a model from disregarding instructions or exploiting a vulnerability, Awad acknowledged. But its goal is to verify an agent’s credentials when it attempts to interact or transact with an outside party.

Without a way to identify themselves, he said, legitimate agents may resort to trying to get around websites’ restrictions just to be able to complete their assigned tasks. Or, they could simply become less useful because they are repeatedly blocked as suspected bots.

Competing to establish a standard

M13 managing partner told ���ϳԹ� News in an interview that he met Awad about a year before his firm invested in Baselayer. At the time, he saw the startup primarily as a provider of Know Your Business technology.

“The business did not feel like a business of the future,” he admits. “It just felt like he was solving a KYB banking verification problem.”

The investor’s view changed as more companies began exploring payments made by AI agents and Baselayer began applying its business-identity data to the field.

“Every agent ultimately is going to have to be tied to something real, and they understand the real world,” Alomar said.

He believes Baselayer’s existing data, identity network and relationships with financial institutions give it an advantage over a startup entering the market from scratch.

“AI agents are rapidly becoming economic actors, but the identity infrastructure underneath commerce was never designed for software that can open accounts, make purchases, move money or enter into transactions on someone else’s behalf,” Alomar added. “That creates an enormous new trust problem, and we believe identity will become one of the foundational infrastructure layers of the agentic economy.”

So far, no dominant standard exists. But Baselayer still must work to persuade agent developers, merchants, financial institutions and payment companies to recognize its credential.

That could take time. Awad said relationships with financial institutions typically take 12 to 18 months to establish, while large merchant partnerships can take up to 24 months. Baselayer may be able to reach some institutions more quickly, however, through its existing reseller relationships.

The company also sees potential use cases beyond payments. For example, Alomar said the technology could eventually authorize agents involved in cryptocurrency transactions or smart contracts, among other things.

“This is not just a fintech business — it’s a security business,” he said. “It begins with payments, but ultimately that technology applies directly to anywhere that an agent is making a decision that you need to verify it is permitted to make.”

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This is a weekly feature that runs down the week’s Top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

It was a monster week for U.S. startup funding, with four companies each raising $1 billion or more. ’s tunnel-drilling company led with a $3 billion Series D, followed by AI coding startup at $2 billion. Joining them near the top was , which landed $1.3 billion for its AI platform for physical operations, while reusable rocket developer raised another $1 billion.

Big checks also flowed to U.S. solar manufacturing, defense tech, legal AI and companies building the chips and networking infrastructure needed for artificial intelligence.

1. , $3B, transportation and infrastructure: Musk’s Bastrop, Texas-based tunneling company raised a $3 billion Series D led by the, with participation from investors including, and. The company is developing underground tunnel networks designed to move passengers and vehicles while reducing surface traffic, and already operates its Vegas Loop system beneath Las Vegas. The latest deal values it at $23 billion and brings its total funding to nearly $3.9 billion, .

2. , $2B, artificial intelligence: San Francisco-based Cognition raised a $2 billion Series E led by,,, and. The company is best known for Devin, its autonomous software-engineering agent, and is part of a highly funded crop of startups betting AI agents will take over increasingly complex coding and development work. Cognition has raised nearly $3.9 billion to date and was valued at $48 billion in the latest round, our shows.

3. , $1.3B, AI for physical operations: San Francisco-based Motive raised $1.3 billion in private equity funding led by. The company, formerly known as KeepTruckin, has an AI-driven platform used by trucking, construction and other physical-economy businesses to manage fleets, monitor driver safety, and automate operations and spending. The latest deal brings Motive’s total funding to just over $2 billion, according to .

4. , $1B, aerospace: Kent, Washington-based Stoke Space raised a $1 billion Series E co-led by and, with among the additional investors. The company is developing fully reusable rockets, including its Nova launch vehicle, as it looks to lower the cost of transporting satellites and other payloads to orbit. The latest round values Stoke at $10 billion and brings total funding to . Its raise adds to the already record-setting sums for space tech startup investment this year.

5. , $835M, solar energy: Norcross, Georgia-based Suniva raised $835 million from investors including, and. The longtime U.S. solar manufacturer produces high-efficiency solar cells and plans to use new capital to expand domestic production, including a new South Carolina facility that would more than quadruple its manufacturing capacity. Suniva has raised nearly .

6. , $600M, defense tech: Huntington Beach, California-based Mach Industries raised a $600 million Series C from investors including and. Founded in 2022, the defense manufacturer develops unmanned aircraft, long-range weapons, propulsion technology and the infrastructure needed to produce defense systems at scale. Mach is part of a broader surge in venture investment into defense companies looking to bring Silicon Valley-style development and manufacturing speeds to military hardware. The latest round values the company at $3.7 billion and brings its total funding to .

7. , $550M, legal AI: San Francisco-based Harvey raised a $550 million Series H co-led by and, with investors including and also participating. Harvey builds generative AI tools for lawyers and other professional-services workers, with products for legal research, document analysis and contract work. The company was valued at $15.5 billion in the latest deal, which brings its total funding to date to nearly . That makes it one of the most well-funded players in the legal tech space, which has seen robust investment this year, though slightly lower than last year’s all-time high.

8. (tied) , $500M, semiconductors: Fab2 raised a $500 million Series A led by, with among the other investors. Formerly known as Atomic Semi, Fab2 is trying to rethink semiconductor manufacturing by designing its own fabrication tools, components and software with the goal of building smaller chip factories faster and more cheaply. The funding is the first disclosed round for the company, which maintains headquarters in California and Kentucky, and values it at $3.7 billion.

8. (tied) , $500M, AI infrastructure: Reno, Nevada-based Positron raised a $500 million Series C led by and, with among its other investors. The startup develops purpose-built hardware for AI inference, where models actually process queries after they have been trained, and is one of a growing crop of chip companies challenging GPUs in particular AI workloads. The latest financing values Positron at $5 billion and brings its total funding to nearly $1.2 billion, .

10. (tied) , $275M, AI networking infrastructure: Laguna Beach, California-based Celero Communications raised a $275 million Series C led by, and. Celero develops coherent digital signal processor technology that helps move enormous quantities of data between chips and data centers while using less power, an increasingly critical bottleneck as AI clusters grow. The round values the company at $3 billion and brings total funding to roughly , according to ���ϳԹ�.

10. (tied) , $275M, biotechnology: South San Francisco, California-based Encoded Therapeutics raised a $275 million Series F led by, with investors including, and also participating. The clinical-stage biotech develops precision genetic medicines for severe neurological disorders, with its lead therapy targeting Dravet syndrome, a rare genetic epilepsy. Encoded has raised $514.1 million to date, .

Methodology

We tracked the largest announced rounds in the ���ϳԹ� database that were raised by U.S.-based companies for the period of Sept. 5-11, 2026. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

Related reading:

• Sector Snapshot: Space Tech Startup Funding Orbits New Highs��
• Anduril Raises Another $5B As Defense Tech Startups Shatter Funding Records
• Sector Snapshot: Legal Tech Funding Down Slightly From All-Time High��
• Sector Snapshot: Semiconductor Startup Funding Still Running Hot

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The highest-valued new entrants were China-based humanoid robotics business , valued at more than $6.3 billion; San Jose, California-based photonics company , valued at $5.5 billion; and Palo Alto, California-based AI model platform , and San Francisco’s semiconductor manufacturing startup , both valued at $5 billion.

AI software featured prominently across model training, assistants, agentic and enterprise workflow automation, coding and voice transcription.

Semiconductors was the second-largest sector, with five new unicorns. Robotics and financial services each added three, while data centers, security and energy each added two.

The U.S. accounted for 16 of August’s new unicorns. China followed with four. South Korea, India, Singapore, the United Arab Emirates, Switzerland, Germany and Turkey each added one. Nigeria and Indonesia also each added one new unicorn — for both, their first new unicorn of the year.

Nine companies exited the ���ϳԹ� in August, per ���ϳԹ� data: Three that went public — the most notable being — and six via acquisition, including , and .

New unicorns in August

Here are August’s new unicorn companies:

AI and software

• , a Palo Alto, California-based platform for training, fine-tuning and deploying custom AI models based on proprietary data, announced $1.1 billion in funding led by and . The less-than-1-year-old company, founded by former co-founder , was valued.
• San Francisco-based , an AI assistant that executes personal tasks, raised a $250 million Series B led by and . The 1-year-old company was valued at $2.5 billion.
• Shanghai-based , a builder of agents for digital and physical environments, raised a $220 million seed round led by and . The less-than-1-year-old company was valued at $2 billion. Its founder, , a researcher, left earlier this year.
• San Francisco-based , which builds AI-powered voice-writing and meeting-transcription tools, raised a $280 million Series B led by , who also led its Series A in 2025. The 5-year-old company was valued at $2 billion.
• San Francisco-based , which provides AI-powered code review and change-management tools, raised a $143 million Series C at a $1.5 billion valuation. and co-led the round. The 3-year-old company said it would commit more than $10 million to keep its tools free for open-source projects over the next year.
• San Francisco-based , which deploys AI agents across calls, email, documents and enterprise systems, raised a $150 million Series C at a $1.2 billion post-money valuation. and led the round. The company is 4 years old, started in logistics and has expanded to insurance, energy, telecommunications and airlines among others and counts 150 enterprise customers.
• Turkey-based , a developer of consumer mobile applications, raised a $50 million Series A led by . The 4-year-old company was valued at $1.25 billion. Its apps include AI chatbot Nova, diagnosing plants with PlantApp, and art generator DaVinci.

Semiconductors

• , a San Jose, California-based developer of photonic interconnects for AI computing infrastructure, raised a $700 million Series C at a $5.5 billion valuation. , , , and led the round. The 2-year-old company is already deployed within data centers.
• raised $400 million in funding led by hedge fund . The 1-year-old company was valued at $5 billion. The San Francisco-based company creates tooling for semiconductor manufacturing and was founded by researchers.
• South Korea-based , which develops edge AI processors for on-device inference, raised about $29 million in the first tranche of its Series D funding from existing investors. The 8-year-old company targeting robotics and electronics was valued at about $2.2 billion.
• Shanghai-based , an AI chip startup for inference, raised a Series A led by local state capital investors and . The 4-year-old company was valued at about $1.5 billion with plans to ship its product in Q4 2026.
• Santa Clara, California-based , which develops low-power silicon and software for AI data centers and physical AI, raised a $110 million Series A led by . The 4-year old company was valued at more than $1 billion.

Robotics

• China-based , which is building the general-purpose IRON humanoid robot, raised more than $900 million in its first outside financing at a post-money valuation exceeding $6.3 billion. led the round, with participation from and support from and Alibaba Group. The company, a subsidiary of public smart electric vehicle company , is 10 years old.
• Singapore-based , which develops robots to operate in real-world environments, raised about $669 million in funding. The 2-year-old company was valued at about $3.3 billion and is set to deploy robots in a Dairy Queen in Shanghai to handle the entire 55-step process of taking orders, preparing the food and handing it to a customer.
• Zurich-based , which develops autonomous technology for heavy construction machinery, raised a $200 million Series A led by . The 4-year-old company was valued at $1 billion and works across multiple construction brands.

Financial services

• Bengaluru-based , a financial-services company spanning payment, lending and insurance, raised $100 million in funding led by . The 7-year-old company was valued at $1.3 billion.
• Berlin-based , a finance AI platform for European mid-sized businesses to�� manage spend, card issuing and expenses, raised a $40 million Series C led by and . The 7-year-old company was valued at around $1.15 billion. The company says it has 5,000 businesses that use the service to give finance teams control.
• Palo Alto, California-based , an AI-native enterprise resource planning platform for accounting, raised a $100 million Series C led by . The 4-year-old company was valued at $1 billion.

Aerospace and defense

• Los Angeles-based , a manufacturer of autonomous military drones and counter-drone systems, raised a $250 million Series C at a $2.5 billion post-money valuation. and the co-led the round. The company is 3 years old. Neros has contracts with the U.S. military as well as half a dozen allied countries.
• Mountain View, California-based , which builds and operates satellite constellations for national security, civil and commercial customers, raised a $250 million Series C led by . The 5-year-old company was valued at $1.5 billion.

Data centers

• Palo Alto, California-based , a vertically integrated AI infrastructure platform, raised a $300 million Series A led by , , and . The less-than-1-year-old company was valued at $2.4 billion. Alongside the equity, Volta secured $5 billion in debt to fund data center buildouts.
• , a full-stack AI infrastructure and neocloud platform, received led by Doha-based broadband provider , which holds a 49% stake. Jakarta-based Zankore is less than 1-year-old and is valued at $1.6 billion. The platform is targeting 1 gigawatt of AI computing capacity.

Security

• San Francisco-based , an AI-native security company that provides autonomous penetration testing, raised a $250 million Series E led by and . The 7-year-old company was valued at $2 billion and is used by 7,000 organizations including defense, Fortune 10, banks and healthcare companies among others.
• Palo Alto, California-based , which provides security for AI agents and third-party applications, raised an $85 million Series D led by . The 9-year-old company was valued at $1.1 billion.

Energy

• China-based , a nuclear fusion company developing small modular reactors, raised about $179 million in seed funding. The 1-year-old company was valued at about $1.5 billion.
• Washington, D.C.-based , which develops software that adjusts AI data-center workloads based on power-grid demands, raised a $150 million Series A at a $1 billion valuation. and co-led the round. The 2-year-old company says the round brings total funding to more than $220 million.

Transportation

• Nigeria-based , a vehicle financing and autonomous fleet management infrastructure, raised a $250 million Series C led by , and . The 7-year-old company was valued at $2.1 billion. It operates a fleet of 42,000 vehicles — both human-driven and autonomous — across 29 cities, with annual recurring revenue of $420 million.��

Critical minerals

• Houston-based , which builds mines and refineries using its MarianaOS software platform, raised a $310 million Series B led by . The 2-year-old company was valued at $1.5 billion.

Web3

• Dubai-based , an AI-enabled stablecoin neobanking platform for cross-border payments and tokenized assets, raised a $68 million Series C led by Tokyo-based at a $1 billion valuation. The 7-year-old company says it processes more than $40 billion in annualized transaction volume.

Related ���ϳԹ� unicorn lists:

• (1,862)
• (658)
• (276)
• (195)
• (119)
• (102)
• (961)
• (547)
• (254)
• (39)
• (489)

Related reading:

• Global Venture Funding Jumps 122% In August As Streak Of Billion-Dollar Deals Continues
• Which Investors Have Backed The Most 2026 Unicorns?
• 40 Companies Joined The ���ϳԹ� In July, The Highest Count In 4 Years

Methodology

The ���ϳԹ� ���ϳԹ� is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on ���ϳԹ� data. New companies are as they reach the $1 billion valuation mark as part of a funding round.��

The unicorn board does not reflect internal company valuations — such as those set via a 409a process for employee stock options — as these differ from, and are more likely to be lower than, a priced funding round. We also do not adjust valuations based on investor writedowns, which change quarterly, as different investors will not value the same company consistently within the same quarter.��

Funding to unicorn companies includes all private financings to companies that are tagged as unicorns, as well as those that have since graduated to .��

Exits analyzed here only include the first time a company exits.��

Please note that all funding values are given in U.S. dollars unless otherwise noted. ���ϳԹ� converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to ���ϳԹ� long after the event was announced, foreign currency transactions are converted at the historic spot price.

Illustration:

This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

AI infrastructure dominated the largest venture rounds this week, with two multibillion-dollar deals in the sector taking the top spots. Data center and cloud provider led with a massive $3 billion financing, followed by ’s $1.5 billion raise. Further down the list, AI inference startup landed $300 million, joining a diverse group of big fundings spanning cybersecurity, robotics, food, HR software, payments and healthcare.

1. , $3B, AI infrastructure: Denver-based Crusoe raised a $3 billion Series F co-led by and, with also participating. Originally founded to use stranded natural gas to power cryptocurrency mining, Crusoe has transformed into a major AI cloud and data center provider serving customers including , and . The company has raised nearly $7.2 billion to date, and the latest financing values it at $30 billion — triple its valuation less than a year ago — according to ���ϳԹ�.

2. , $1.5B, AI infrastructure: New York-based Fluidstack raised $1.5 billion in a private equity round led by, bringing the AI infrastructure company’s total funding to just over $2.6 billion. Fluidstack provides large-scale GPU and data center infrastructure for demanding AI workloads and has emerged as one of a growing group of companies spending heavily to meet soaring compute demand for AI. The financing values the company at $18 billion.

3. (tied) , $300M, AI infrastructure: San Francisco-based Gimlet Labs raised a $300 million Series B led by, with investors including ,, and . Gimlet is building an AI inference cloud that distributes workloads across different types of chips, an approach aimed at making the increasingly compute-intensive process of running AI models faster and more efficient. The company has raised $392 million to date and was valued at $3 billion in the latest round, .

3. (tied) , $300M, cybersecurity: San Francisco-based Upwind Security raised $300 million in new funding co-led by and. Other investors included 1,, and . The company’s platform uses real-time cloud runtime data to identify threats and vulnerabilities, putting it at the intersection of two particularly well-funded areas: cloud security and AI. Upwind has raised $730 million to date and was valued at $3.8 billion in this latest deal.

5. , $250M, food and nutrition: New York-based high-protein food company David raised a $250 million Series B co-led by and., and company co-founder also participated. Best known for its high-protein, low-calorie bars, David has expanded into other protein-focused foods as consumers continue gravitating toward products marketed around protein and metabolic health. The company has raised $335 million and was valued at $2.25 billion in the latest round.

6. , $166M, HR software: New York-based HiBob raised $166 million in a round led by, with also participating. HiBob’s Bob platform combines HR, payroll, benefits and employee-management tools, and the company is increasingly positioning its workforce data as a foundation for enterprise AI applications. The latest deal brings its total funding to $740 million and values the company at $3.2 billion.

7. , $165M, robotics and physical AI: Sunnyvale, California-based Lyte AI raised a $165 million Series C led by, with participation from,, and. Founded by former engineers, Lyte develops custom silicon, sensors and AI software that help robots perceive and understand their surroundings, the kind of technology that underpins the fast-growing physical AI sector. Lyte has now raised $272 million to date, , and was valued at $1.6 billion in the Series C.

8. , $155M, fintech and payments: Mountain View, California-based TabaPay secured $155 million in growth financing led by. The company provides money-movement infrastructure that helps banks and fintech companies instantly disburse, collect and transfer funds. The company announced the latest funding as it also of federally chartered , a move that could deepen its role in payments infrastructure. TabaPay’s new round follows a Series A of an undisclosed amount back in 2022.

9. , $125M, health care and oncology: Nashville, Tennessee-based Thyme Care raised a $125 million Series E led by , the healthcare investment arm of . Other backers included, and, among others. Thyme Care works with health plans, employers and providers to coordinate cancer treatment and manage oncology care, part of a broader shift toward value-based specialty care. The company has now raised $399 million in total and was valued at $2 billion in the latest round.

10. , $100M, AI cybersecurity: Austin-based HiddenLayer raised a $100 million Series B led by.,, and also participated. HiddenLayer builds security tools designed specifically to protect AI models, agents and workflows from attacks and vulnerabilities, a category gaining urgency as enterprises move AI systems into production. The company has raised $156.2 million to date, .

Methodology

We tracked the largest announced rounds in the ���ϳԹ� database that were raised by U.S.-based companies for the period of Aug. 29-Sept. 4, 2026. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

Related reading:

• Former Apple Engineers’ Physical AI Startup Lyte Raises $165M At $1.6B Valuation
• VCs Pour Billions Into Physical AI As The Next Wave Of AI Investing Takes Shape

Illustration:

The Incline Village, Nevada-based company is also acquiring Austin-based agentic AI startup as it looks to automate more of the labor-intensive work involved in investigating financial crime.

led the investment, which includes both primary capital and a secondary tender offer for employees. , , and others also participated. Socure did not disclose the terms of its acquisition of Fravity.

With the latest funding, Socure has raised over $742 million in disclosed funding since its 2012 inception. It was previously valued at $4.5 billion at the time of its Series E round in 2021. The company did not break down how much of its raise was primary and secondary capital.

Rapid growth as fraud surges

The transactions come as Socure says it is seeing both rapid growth in its own business and a sharp rise in increasingly sophisticated fraud. The company is refreshingly open about its financials, telling ���ϳԹ� News that it ended the second quarter with $364 million in annual recurring revenue, up 63% from a year earlier, and added 95 customers during the quarter, including , , and . It also claims to be growing “profitably.”

Socure uses AI and machine learning to help banks, fintechs and government agencies verify identities so they can “approve real customers instantly while stopping fraud.”

It now has more than 3,000 enterprise customers. They include 19 of the 20 largest U.S. banks, more than 600 fintech companies, major sportsbook and prediction-market operators, and 160 public-sector organizations. Specifically, some of those customers include , , , , and . The company’s revenue model mixes usage- and transaction-based SaaS.

AI creates both an opportunity and a problem

Socure co-founder and CEO said AI is creating both an opportunity and a problem for the business. For example, Socure saw an 8,000% increase in AI-driven fraud across its network last year, according to the company, as generative AI and other tools make it easier to create convincing fake identities and automate attacks.

At the same time, AI could help address one of the more costly parts of fraud prevention: investigating the large number of cases and alerts that automated systems flag for human review.

That is where Fravity comes in.

Automating fraud investigations

Fravity has built an AI-native platform that uses agents to automate fraud, risk and compliance investigations. Its technology will be incorporated into Socure’s RiskOS platform as RiskOS_Agents, initially focusing on watchlist screening and monitoring and know-your-business checks.

Socure and Fravity already share several enterprise customers that use the two products together, according to Socure. Across its existing deployments, Fravity has reduced cost per case by 80%, sped up case resolution fivefold and cut false positives by as much as 70%, the companies say.

The acquisition puts Socure more directly into what identity intelligence company estimates is a $71.1 billion financial crime investigation market. The problem is particularly acute at banks, where 53% spend at least an hour reviewing each alert, and 37% manually review more than 40% of alerts, according to Liminal.

As AI increases the volume and sophistication of fraud, Ayers argues that the identity layer — determining whether people and increasingly AI agents are who or what they claim to be — is becoming more critical to doing business online.

“I believe there are two types of companies that matter in the AI-driven global economy: those that are AI-native, and those that fight the consequences of AI acceleration,” he said in a statement.

Expanding beyond financial services

The investment follows a period of expansion for Socure beyond its financial services roots. In May, the company won a five-year, $163 million federal contract to provide identity-proofing technology for Login.gov. It is also pushing further internationally.

Socure had more than 550 employees as of March 2026, more than 100 more than it had about a year ago, according to Ayers.

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This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

Startups raised funding rounds with a lot of zeroes at the end this week. Three companies — , and — secured financings of $1 billion or more. Additionally, a robust lineup of companies in sectors including AI, e-commerce, cybersecurity, biotech and even mining also announced sizable new rounds.

1. , $1.37B, manufacturing: Hadrian, a developer of highly automated factories, raised $1.37 billion in Series D funding led by , , , , and . The financing sets a $7.87 billion valuation for the 6-year-old, Torrance, California-based company.

2. (tied) , $1B, energy storage: Austin-based Base Power, a developer of residential battery energy storage systems, secured $1 billion in Series D financing at a $13 billion post-money valuation. , , and led the financing, which coincided with the launch of the company’s Base Core home battery.

2. (tied) , $1B, nuclear power: Valar Atomics, a developer of technology and infrastructure to deliver nuclear energy, closed on $1 billion in Series B funding led by . The El Segundo, California-based company also secured a $200 million credit facility led by and .

4. , $700M, AI connectivity: Lumilens, developer of a connectivity platform for AI infrastructure, emerged from stealth and announced more than $700 million in new funding. , , , and led the financing for the San Jose, California-based startup.

5. , $545M, live shopping: Live shopping marketplace Whatnot bagged $545 million in Series G funding. The round reportedly a $20 billion valuation for the Los Angeles-based company, with , and as lead investors.

6. , $310M, critical minerals: Mariana Minerals, a software-focused developer of projects for supplying critical minerals, picked up $310 million in Series B financing led by . The 4-year-old company engineers, builds and operates mines and refineries using its software platform.

7. , $300M, AI infrastructure: Volta, a developer of AI cloud infrastructure, from stealth and said it raised a Series A at a $2.4 billion valuation, led by , , and .

8. , $250M, cybersecurity: San Francisco-based cybersecurity provider Horizon3, announced a $250 million Series E. and led the round, which set a valuation of more than $2 billion, triple the value set for its Series D last year.

9. , $188M, biotech: Watertown, Massachusetts-based drug discovery startup LifeMine Therapeutics secured $188 million in Series E funding led by . The funding will go toward clinical development of its lead program and advance its pipeline of transplantation and immunology therapies.

10. , $150M, agentic AI: HappyRobot, developer of an agentic AI platform geared for enterprises in sectors including logistics, financial services, utilities and manufacturing, raised $150 million in Series C funding led by and .

Methodology

We tracked the largest announced rounds in the ���ϳԹ� database that were raised by U.S.-based companies for the period of Aug. 1-7. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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It is difficult to define the extent to which a specific company should morph itself into an “AI native” company. Does this add value for everyone?

AI does not automatically increase exit value. In some cases, it can reduce differentiation, compress margins, complicate diligence and make a company more difficult to acquire. Like pricing, customer service or go-to-market strategy, AI requires a careful balancing act between speed and defensibility, innovation and complexity, short-term productivity and long-term strategic value.

Let’s jump into three ways AI strategy can impact exit value.

Build an AI architecture that acquirers can trust

Many startups are rapidly adding AI copilots, model integrations, orchestration layers, prompt libraries, vector databases and third-party AI tools across the organization. This may accelerate product development and help teams ship faster. However, from the perspective of an acquirer, it can also create a more complicated architecture.

During due diligence, buyers care about how AI is being used. Which models are embedded in the product? Which vendors are critical to delivery? Where does customer data flow? How are outputs monitored? What happens if pricing changes, APIs break or regulation shifts?

A startup may see AI adoption as innovation. A buyer may see it as integration complexity, vendor dependency, compliance exposure and security risk.

This is especially important for strategic acquirers that need to integrate the target into a larger platform. If AI makes the product easier to scale, automate, secure and maintain, it can support valuation. If it creates a fragile layer of external dependencies, unclear data flows and difficult-to-audit decision-making, it may reduce confidence and lower the price a buyer is willing to pay.

Invest in proprietary data

Even one year ago, adding AI functionality to a product could create excitement by itself. Today, many AI features are becoming easy to replicate. Summarization, search, chat interfaces, recommendations, content generation and workflow assistance are increasingly available through the same underlying models and infrastructure. This matters for exits.

A strategic acquirer rarely pays a premium simply because a startup integrated the latest model. They pay for what they cannot easily build themselves: proprietary datasets, unique customer workflows, strong distribution, deep vertical adoption or network effects that improve with scale.

Founders should therefore ask a simple question: Is our AI strategy creating a defensible asset, or are we just adding features that competitors can copy within weeks or months?

Revisit your buyer map as AI redraws strategic boundaries

Historically, many companies built their exit strategy around a familiar buyer map. A cybersecurity startup might sell to a larger cybersecurity vendor. A vertical SaaS company might sell to a competitor in the same industry. A workflow automation company might sell to a productivity platform. AI is changing those boundaries.

As AI expands what platforms can do, strategic buyers are moving into adjacent markets they previously ignored. An infrastructure company may acquire an identity platform because AI agents need secure access controls. An ERP vendor may acquire workflow automation because AI is moving closer to business process execution. A data platform may acquire a vertical application because domain-specific data is becoming more valuable.

This means CEOs should revisit their buyer map every six to 12 months. The most logical acquirer today may not be the same one that would have been logical even one year ago.

is a strategic adviser to tech companies, investors, CEOs and boards, specializing in strategy, growth and M&A. He is a guest contributor to ���ϳԹ� News and a university lecturer on strategy, finance and entrepreneurship. Learn more at and connect with him on .

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July funding was flat month over month, following on the heels of a record-breaking first half of 2026, when startups raised $515 billion globally.

Thirteen startups raised billion-dollar rounds in July, the highest count in a single month, though not the largest amount raised in such deals, an analysis of ���ϳԹ� data shows. The tally includes eight U.S.-based companies, two each from Germany and China, and one company headquartered in Singapore.

, a frontier lab founded by former Chief Scientist , reportedly raised $5 billion from . The next two largest deals were Beijing-based frontier lab ’s $3.5 billion raise after releasing its latest Kimi K3 model, and raising $2.8 billion for short-video generation.

Two Germany-based companies in defense tech also raised billion-dollar rounds: and . In the U.S., companies that raised billion-dollar-plus rounds spanned the energy, industrial robotics, AI training, security and semiconductor industries.

Funding to AI

A total of $35 billion, or around 63% of global venture funding, went to AI-focused companies in�� July. Other leading sectors were aerospace, defense and energy.

U.S.-based companies raised a total of $29 billion, or around 52% of global venture capital, last month with more than 60% of capital invested in its AI-focused companies.

Exits

July was also a robust month for startup exits, including via acquisition and public-market debuts.

Venture-backed M&A totaled more than $9 billion in July, with five companies exiting at prices�� over $1 billion, ���ϳԹ� data shows. Notable acquisitions included London-based data center provider ’s roughly $1.65 billion acquisition of software layer , which was built to manage AI workflows, and in the security sector, AI-native security company ’s $1 billion acquisition of , a service to manage non-human identities.

Twelve venture-backed companies went public above $1 billion in value in July, including five from China, six U.S.-based companies, and one from Italy. The largest was Chinese chipmaker , which went public at around $85 billion and . Italy-based , an acquirer of software companies including and , went public at a value of $18.5 billion. And last-mile transportation company , founded in 2017, went public at $1.6 billion in value, raising $167 million in the process.

In closing

If the first half of 2026 established that venture has entered a new era of mega-financings, July reinforced that the trend is broadening rather than fading. Record numbers of billion-dollar rounds in both hardware and software, alongside a healthy IPO and M&A market, point to an ecosystem where capital is not only concentrating in category leaders but is also beginning to recycle through exits.

Correction: The monthly funding totals in this article were revised to reflect in-progress funding rounds.

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Methodology

The data contained in this report comes directly from ���ϳԹ�, and is based on reported data. Data is as of Aug. 3, 2026.

Note that data lags are most pronounced at the earliest stages of venture activity, with seed funding amounts increasing significantly after the end of a quarter/year.

Please note that all funding values are given in U.S. dollars unless otherwise noted. ���ϳԹ� converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to ���ϳԹ� long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. ���ϳԹ� also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less.

Early-stage consists of Series A and Series B rounds, as well as other round types. ���ϳԹ� includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

Late-stage consists of Series C, Series D, Series E and later-lettered venture rounds following the “Series [Letter]” naming convention. Also included are venture rounds of unknown series, corporate venture and other rounds above $15 million. Corporate rounds are only included if a company has raised an equity funding at seed through a venture series funding round.

Technology growth is a private-equity round raised by a company that has previously raised a “venture” round. (So basically, any round from the previously defined stages.)

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It’s a worry that spilled over into headlines last week, after an agent the open-source AI platform . Turns out rogue AI agents causing mayhem is no longer�� a hypothetical problem.

Seed investors apparently saw this coming, judging by the plethora of good-sized rounds for companies at the intersection of AI and security. Startups in this cohort have raised $855 million across more than 150 reported seed-stage rounds this year, per ���ϳԹ� data. That puts investment on track for an all-time high.

A large cluster of deals in the $5M to $10M range

Here at ���ϳԹ� News, we took a particular interest in seed rounds in the $5 million to $10 million range, an area where cybersecurity investment was particularly robust.

Why this size range? It started as a broader data dive focused on top themes for mid-sized seed rounds, an often overlooked subset in a startup funding climate dominated by AI megadeals.��

An initial perusal indicated cybersecurity warrants a standalone analysis. We found both a high number and a wide breadth of funded companies in the space, with missions ranging from identifying AI hallucinations to building adversary simulations to verifying agents in finance.

To illustrate, below is a sample list of 14 AI-focused security companies that raised seed financings this year in our target range.

Big seed and early-stage bets too

We also had some large rounds in the mix, indicating investors saw risk-reward compelling enough to write big checks for newly minted startups. Some of the biggest included:

• , a developer of identity intelligence technology for the AI era, secured $60 million in a seed financing this month.
• , a Silicon Valley startup working on an AI-native cybersecurity platform that doesn’t depend on the public cloud, raised $45 million in a March seed round.
• , an upstart developing an AI governance and security platform for enterprises, in March with $34 million in a seed round it described as massively oversubscribed.��

When investors place larger bets at seed, there’s usually at least one of two core reasons. The first is that the founder or founding team is impressive enough that backers are willing to invest primarily on the mission and people. The second is that the startup has demonstrated impressive traction with its earliest efforts.

For larger rounds, we’re seeing a number of the first category. Cylake’s founder and CEO, for example, is , founder of . JetStream, meanwhile, has drawn veterans of , and other security leaders.��

A solid year for overall security funding

Notably, the strong cybersecurity seed funding environment coincides with solid overall venture investment levels. In the first half of the year, per ���ϳԹ� data, startups in the sector pulled in $10.6 billion in financing across stages, roughly in line with recent prior comps.

That said, seed may be where excitement is greatest. With hundreds of billions flowing into building AI infrastructure and applications in recent quarters, someone will have figure out innovative ways to keep myriad real-life and hypothetical AI security nightmares from coming true.��

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