Executive Intelligence · The Term Sheet · November 7, 2026
The Venture Capital Race for Enterprise AI: Where Are Investors Placing Their Bets? — capital concentration, agent platforms, infrastructure financing, vertical AI, and the investors shaping the next generation of enterprise technology.
The Central Question — and Why “Enterprise AI” Is Not One Market
Venture capital firms deployed more than $500 billion into AI companies in the first nine months of 2026, already eclipsing the whole of 2025. A handful of foundation-model labs and infrastructure platforms absorb the majority of dollars, while a second tier of application, agent, and vertical companies compete for the remaining capital under much tighter scrutiny of commercial traction. In the first quarter alone, AI startups raised $255.5 billion — surpassing the full-year 2025 total in a single quarter — and AI captured 80% to 88% of all global venture funding. Those aggregate figures describe a capital market that has reoriented itself almost entirely around a single technology.
This Special Report examines who is financing the next generation of enterprise AI companies, which segments are attracting the strongest investment conviction, and how capital is shaping the competitive landscape across platforms, agents, infrastructure, and vertical applications.
But the aggregate obscures the structure. Two foundation-model companies — OpenAI and Anthropic — absorbed a combined $187 billion in primary capital in 2026, with OpenAI’s $122 billion round alone accounting for roughly 43% of all Q1 venture deployment. Strip those two out and the enterprise AI market looks very different: a set of application companies (Sierra, Harvey, Glean, Decagon, Cognition) with proven revenue and valuations that are high but tethered to commercial traction; an infrastructure layer (Databricks, Crusoe, Together AI, Lambda) raising enormous rounds against revenue run-rates; and a security layer where the defining event was not a funding round but a $32 billion acquisition.
The central editorial question is not “how much capital is flowing into enterprise AI” — it is “which layers of the enterprise AI stack are attracting capital on terms that reflect durable businesses, and which are attracting capital on terms that reflect narrative.” This report examines the companies, the investors, the funding structures and the commercial evidence behind each layer.
Editorial Note: This report distinguishes primary equity funding from secondary transactions and debt facilities, and announced rounds from completed closings where the distinction is material. Valuations are reported as disclosed by the companies or their investors. Revenue figures are company-reported and unaudited unless otherwise stated. Where a company is described as “enterprise AI,” that designation reflects the primary customer base, not a claim that the company sells exclusively to enterprises.
1. The Macro Picture — Capital Concentration Is the Defining Feature
The headline numbers are extraordinary by any historical standard. Global AI investment reached approximately $430 billion in the first half of 2026 alone, exceeding the whole of 2025, according to EY. PitchBook recorded $255.5 billion in Q1 2026 AI venture funding, the highest single quarter on record, with three deals accounting for 67% of the capital deployed. By Q3, the pace had slowed — a “sharp slowdown” relative to the first half — but the cumulative figure still passed $500 billion for the year to date.
That concentration is the most important structural fact in this report. AI captured roughly 80% of all global venture capital in Q1 2026, and within that AI total, foundation-model companies took the overwhelming majority. One analysis estimates that of the roughly $242 billion deployed to AI in Q1, approximately $180 billion went to foundation models and infrastructure, with about $62 billion to application-layer companies including agents. Enterprise AI is therefore competing for capital within an asset class that is itself dominated by two or three companies.
The concentration paradox
Enterprise AI is attracting record capital — but the distribution of that capital is extreme. Two foundation-model companies raised $187 billion in 2026. The largest enterprise application round — Cognition’s $2 billion Series E — is roughly 1.6% the size of OpenAI’s round. The application layer is where commercial traction is proven; it is not where capital is most abundant.
2. Foundation Models — The Two-Body Problem
In 2026, AI funding reached historic levels. Multiple trackers show hundreds of billions of dollars deployed year-to-date, with AI representing the dominant share of global venture dollars (frequently reported above 60–70% in recent quarters). The top of the market is extreme: Anthropic raised $65 billion in Series H funding at a $965 billion post-money valuation, led by Altimeter Capital, Dragoneer, Greenoaks and Sequoia Capital, with co-leads including Capital Group, Coatue, D1 Capital Partners, GIC, ICONIQ and XN. The round included $15 billion from hyperscaler commitments, of which Amazon contributed $5 billion, and strategic participation from Samsung, SK hynix and Micron. At $965 billion, Anthropic is valued at roughly 20.5x revenue — a multiple that implies investors expect the company to become one of the largest software businesses in history.
OpenAI closed a $122 billion round at an $852 billion post-money valuation in late March 2026 — the largest private financing in Silicon Valley history. Amazon invested $50 billion, its largest single investment in any company, with Nvidia also participating. Bloomberg reported that the round was initially structured at $110 billion at a $730 billion pre-money valuation before being upsized. OpenAI has signalled that it may file for an IPO as early as the second half of 2026.
The investor composition of these rounds is the most revealing detail. Both rounds are dominated by crossover investors and strategic corporates — sovereign wealth funds, hyperscalers, memory manufacturers — rather than by traditional venture firms. Sequoia and Altimeter led Anthropic; Amazon and Nvidia anchored OpenAI. That structure tells you that the foundation-model layer is no longer a venture-capital market. It is a strategic capital market, in which the investors are also the suppliers, the customers, or the distribution partners. Venture firms participate, but they are not setting the price.
These two AI companies alone accounted for a very large fraction of total AI venture dollars in the first half of the year. Below the frontier labs, capital still flows in large absolute amounts but becomes more selective. Databricks, CoreWeave, Crusoe, Together AI, Baseten, and similar infrastructure players have raised multi-billion-dollar equity and debt packages. Application-layer leaders such as Glean, Harvey, Sierra, and Decagon have also secured substantial late-stage rounds, though at far smaller absolute sizes than the model labs.
| Company | Round | Valuation | Lead / anchor investors |
|---|---|---|---|
| Anthropic | $65B Series H | $965B post-money | Altimeter, Dragoneer, Greenoaks, Sequoia; Amazon, Samsung, SK hynix, Micron |
| OpenAI | $122B | $852B post-money | Amazon ($50B), Nvidia; crossover and sovereign capital |
3. Enterprise AI Platforms — Where Commercial Traction Is Proven
The application layer is where enterprise AI becomes a business rather than a capability. The companies here sell software that enterprises deploy into workflows, and their valuations — while high — are anchored to disclosed revenue.
Sierra, the customer-experience AI platform co-founded by Bret Taylor and Clay Bavor, raised $950 million in Series E funding at a $15.8 billion post-money valuation, led by Tiger Global and GV, with Benchmark, Sequoia and Greenoaks participating. The round brought total capital raised past $1 billion and tripled Sierra’s valuation from $4.5 billion eighteen months earlier. Sierra reported more than $150 million in ARR as of February 2026 and serves over 40% of the Fortune 50, including Prudential, Cigna, Blue Cross Blue Shield, Rocket Mortgage and one in three of the world’s largest banks.
Harvey, the legal AI platform, raised $550 million at a $15.5 billion valuation in September 2026, co-led by Lightspeed Venture Partners and Diffusion, with new investors Sapphire Ventures, Whale Rock Capital and Verified Capital joining existing backers Sequoia, Kleiner Perkins, Andreessen Horowitz, Coatue, Conviction, Elad Gil, Evantic, GIC, Goldman Sachs Alternatives and WndrCo. Harvey disclosed $400 million in ARR, more than 3,000 customers, coverage of 80% of the top 100 law firms and a fifth of the Fortune 500, and the acquisition of Guardrails AI — its fourth acquisition of 2026. The valuation was nearly double the $11 billion set in March 2026.
Glean, the enterprise search and AI assistant platform, is valued at $7.2 billion on $774.5 million in total funding, with investors including Sequoia, General Catalyst, Kleiner Perkins, Lightspeed, ICONIQ, Altimeter, Coatue and Wellington Management. Glean has reportedly surpassed $300 million in ARR. Writer is valued at $1.9 billion on $326 million raised, backed by Premji Invest, Radical Ventures, ICONIQ and Insight Partners.
Decagon raised $250 million in Series D funding at a $4.5 billion valuation in January 2026, led by Coatue and Index Ventures, with a16z, Accel and Bain Capital participating. The company subsequently closed an employee tender at the same valuation and has reportedly hired a banker to evaluate acquisition interest.
The application-layer verdict
The application layer is where enterprise AI has demonstrated commercial traction — Sierra at $150M+ ARR, Harvey at $400M ARR, Glean at $300M+ ARR. These are real businesses with real customers. But the valuations are demanding: Sierra at roughly 105x ARR, Harvey at roughly 39x ARR, Glean at roughly 24x ARR. Those multiples assume years of high growth and defensibility against both incumbent software vendors and foundation-model companies moving up the stack.
4. AI Agents — The New Investment Category
AI agents have become a distinct venture category in 2026. In the first week of May alone, venture capital deployed $2.1 billion into AI agent companies, according to Big Sky Capital. The category spans coding agents, customer-service agents, sales agents and general-purpose autonomous workflows.
Cognition, the company behind the Devin coding agent, raised over $2 billion in Series E funding at a $48 billion valuation in September 2026, led by Andreessen Horowitz and Accel, with Founders Fund, General Catalyst, Kleiner Perkins, T. Rowe Price, Altimeter, Bessemer, Ribbit, Valor, Greylock, Alkeon and Meritech participating. The round nearly doubled the $26 billion valuation set in May 2026, when the company raised $1 billion. Cognition reported $900 million in revenue — a figure that, at a $48 billion valuation, implies a 53x multiple.
The agent category is attracting capital because it represents a different commercial model from both copilots and foundation models. A copilot assists a human; an agent performs work. That shift changes the pricing unit — from per-seat to per-outcome — and it changes the buyer — from the individual user to the operations leader with a budget for headcount or outsourced services. The open question is whether the technology can deliver reliable outcomes at the reliability enterprises require. One industry analysis noted that 88% of agent deployments never reach production — a statistic that should temper the enthusiasm implied by the funding totals.
5. AI Infrastructure — The Capital Sink
The Infrastructure layer has absorbed enormous capital, often structured as a mix of equity, private credit, and GPU-backed or contract-backed debt.
Databricks closed a $5 billion strategic funding round at a $190 billion valuation in August 2026, led by Coatue with participation from Blackstone, MGX, T. Rowe Price, JPMorgan Asset Management, Fidelity, NEA, Ontario Teachers’, GIC, Premji Invest, Sixth Street, Andreessen Horowitz, Insight Partners and Goldman Sachs Asset Management. The company reported surpassing a $7 billion revenue run-rate in Q2 2026, growing more than 80% year over year — a multiple of roughly 27x revenue. Databricks had already raised about $5 billion in equity and $2 billion in debt at a $134 billion valuation earlier in 2026.
Crusoe, the vertically integrated AI infrastructure company, raised $3.9 billion in Series F funding at a $30.9 billion post-money valuation in September 2026, led by Atreides Management and Mubadala Capital, with Qatar Investment Authority participating as a strategic investor. Together AI raised $800 million in Series C funding at an $8.3 billion valuation in July 2026, led by Aramco Ventures with participation from Nvidia, Salesforce Ventures, General Catalyst, Vista Equity, Emergence Capital, March Capital, Lux Capital, S Ventures and Schneider Electric. Together AI secured commitments for more than 500 MW of additional compute capacity as part of the round, financed separately.
Lambda Labs is reportedly raising up to $4 billion at a $14.5 billion pre-money valuation ahead of a planned 2027 IPO, led by Blackstone and Coatue. Lambda’s AI compute backlog grew from $15 billion in June 2026 to $50 billion in September 2026. Scale AI is valued at $29 billion following Meta’s $14.3 billion investment for a 49% stake in June 2025. CoreWeave has raised billions in equity and debt, with Nvidia as a repeat investor and Blackstone and Magnetar leading a $2.3 billion debt facility. Developer platforms (Hugging Face, Weights & Biases, Anyscale, and others) receive steady but smaller absolute capital relative to pure compute providers. Private credit and infrastructure-style financing have become as important as traditional venture equity for the largest GPU-cloud players. This creates both opportunity (faster capacity build-out) and risk (leverage and refinancing exposure if utilization or pricing softens).
The infrastructure verdict
Infrastructure is absorbing the largest enterprise-adjacent cheques, but the capital structure is changing. Together AI’s $500M+ compute commitment is financed separately from its equity round. Lambda’s raise is structured around a 2027 IPO. CoreWeave’s growth is funded substantially through debt. The infrastructure layer is becoming a capital-markets business, not a venture business — and that changes the risk profile for every investor in it.
6. AI Security — The Exit-Driven Category
As enterprises move from pilots to production, venture capital has flowed into companies that address data access, security, compliance, and agent governance. Firms such as Wiz, Snyk, Vanta, Cyera, Protect AI, HiddenLayer, and Sentra have raised or expanded rounds. Investors view AI-specific security and governance as both a necessary enabler of broader enterprise AI adoption and a relatively durable software category less exposed to model commoditization.
The defining event in enterprise AI security in 2026 was not a funding round. It was Google’s $32 billion all-cash acquisition of Wiz, completed in March 2026 — the largest venture-backed acquisition in history. Index Ventures, Wiz’s largest outside shareholder at 12%, collected roughly $3.8 billion; Sequoia’s 10% stake translated to approximately $3.2 billion; Insight Partners held a stake worth about $2.9 billion. Salesforce Ventures, an investor in Wiz, described the outcome as “one of the most significant exit outcomes in Salesforce Ventures’ history”.
The Wiz exit has reshaped the category’s investment logic. Cyera, the AI and data security company, raised $600 million in Series G funding at a $12 billion valuation in June 2026, led by Evolution Equity Partners with Cyberstarts and Temasek participating, and subsequently secured an additional $400 million from Goldman Sachs at the same valuation. Vanta, the compliance and trust management platform, is valued at $4.15 billion on a $150 million Series D led by Wellington Management, and has surpassed $300 million in ARR as “shadow AI” adoption drives demand. Snyk is valued at $7.4 billion following a $196.5 million Series G.
The smaller end of the category tells a different story. Protect AI raised roughly $108 million before being acquired by Palo Alto Networks in 2025. HiddenLayer has raised approximately $56 million and is reportedly raising a $100 million Series B. The gap between the category leaders and the specialists reflects a structural reality: AI security is being absorbed into platform vendors — Palo Alto’s Prisma AIRS, CrowdStrike’s Falcon, Microsoft Defender — rather than sustaining a large population of independent companies.
7. Vertical AI — The Defensibility Question
Vertical AI (legal, healthcare, insurance, financial services, customer support) continues to attract strong conviction when companies show domain expertise, proprietary data or workflows, and enterprise contracts. Harvey (legal), Abridge (healthcare), Kalepa (insurance), and Sierra/Decagon (customer experience) illustrate the pattern. General-purpose platforms remain a competitive threat, so investors favor companies with clear workflow lock-in or regulatory/data advantages.
Harvey in legal and Abridge in healthcare are the clearest examples. Abridge has raised approximately $830 million, most recently a $316 million Series E extension in April 2026 at a $5.3 billion valuation, with Nvidia’s NVentures among the investors. The company’s revenue has grown from roughly $60 million in 2024 to $170 million+ in 2025, with a forecast of $350–400 million in 2026. Kalepa raised $75 million in Series B at a $470 million valuation for AI underwriting and insurance portfolio management, led by Updata Partners, with IA Ventures and Inspired Capital participating.
The vertical AI thesis is commercially sound — regulated industries pay for workflow software that reduces risk and improves throughput. The investment question is whether vertical specialists can defend their position as foundation-model companies add industry-specific capabilities and as incumbent vertical software vendors embed AI into their existing products. Harvey’s 39x revenue multiple and Abridge’s 13–15x forward revenue multiple both assume the specialists win that argument.
8. The Investor Landscape — Who Is Writing the Cheques
The investor base for enterprise AI is broader and more stratified than it was two years ago. Four distinct groups are active, and they invest on different logic.
Traditional venture firms — Andreessen Horowitz, Sequoia, Accel, General Catalyst, Lightspeed, Kleiner Perkins, Bessemer, Greylock, Index, Khosla, Radical, Menlo — are most active at the application and early-growth stages. a16z led Cognition’s Series E and TypeSafe’s $870 million Series A, and holds positions in Databricks and Harvey. Sequoia led Anthropic’s Series H and holds Glean, Harvey, and Wiz. General Catalyst participated in Glean and Together AI. These firms are competing for allocation in a market where the largest rounds are increasingly dominated by non-venture capital.
Corporate venture arms are the most strategically significant investors in the ecosystem because their capital often comes with commercial relationships. Nvidia’s NVentures has invested across the stack — Together AI, CoreWeave, Abridge, Legora, Databricks, Cohere, Mistral, Figure AI — and its participation is often a signal that the portfolio company will consume Nvidia GPUs. Salesforce Ventures has backed Anthropic, Together AI, Mistral, Sakana AI, 8090 Labs and Wiz, often with co-marketing or integration agreements attached. GV (Google Ventures) co-led Sierra’s Series E. M12 (Microsoft’s fund) backed HiddenLayer’s Series A. These investors are not neutral — their capital is a commercial signal.
Crossover and sovereign investors — Coatue, Altimeter, Tiger Global, T. Rowe Price, Fidelity, GIC, Mubadala, Qatar Investment Authority, MGX, Temasek — are now the marginal price-setters for late-stage enterprise AI. Coatue led Databricks at $190 billion and Decagon at $4.5 billion, and participated in Cyera and Anthropic. Tiger Global co-led Sierra at $15.8 billion. Mubadala co-led Crusoe at $30.9 billion. These investors apply public-market comparables and are more sensitive to revenue quality and path to profitability than earlier-stage VCs.
Growth equity and private equity — Blackstone, Vista Equity, Sixth Street, Insight Partners — are entering enterprise AI at the later stages, often through structured equity or debt. Blackstone participated in Databricks and led Lambda’s pre-IPO round with Coatue. Vista Equity participated in Together AI. The presence of these investors signals that enterprise AI is maturing into an asset class that can absorb large cheques without requiring venture-style risk tolerance.
| Investor | Type | Notable enterprise AI positions | Investment logic |
|---|---|---|---|
| Andreessen Horowitz | VC | Cognition (lead), Databricks, Harvey, TypeSafe | Frontier technology and category-defining platforms |
| Sequoia Capital | VC | Anthropic (co-lead), Glean, Harvey, Wiz | Foundation models and application leaders |
| Coatue | Crossover | Databricks (lead), Decagon (co-lead), Cyera, Anthropic | Late-stage growth with public-market discipline |
| Tiger Global | Crossover | Sierra (co-lead) | Category leaders with proven enterprise traction |
| General Catalyst | VC | Glean, Together AI, Cognition | Platform and infrastructure companies with network effects |
| Nvidia (NVentures) | Corporate VC | Together AI, CoreWeave, Abridge, Databricks, Cohere | Ecosystem development and GPU demand creation |
| Salesforce Ventures | Corporate VC | Anthropic, Together AI, Mistral, Sakana AI, Wiz | Strategic adjacencies and integration opportunities |
| Mubadala / QIA | Sovereign | Crusoe (co-lead) | Long-duration infrastructure exposure |
9. Strategic Assessment — Where the Durable Businesses Are
The enterprise AI market is not one race. It is at least four, and the investment logic differs in each.
Foundation models are a capital-markets game. OpenAI and Anthropic have raised enough to fund years of compute and research, and their investors are strategic partners rather than financial sponsors. The risk is not that they fail to build capable models; it is that the returns required to justify an $852 billion or $965 billion valuation may not materialise within the time horizons of their investors. This is not an enterprise AI investment in the venture sense. It is a bet on a new utility.
Enterprise applications — Sierra, Harvey, Glean, Decagon, Writer — are where commercial traction is demonstrable. These companies have real ARR, real enterprise customers and real renewal cycles. Their risk is defensibility: incumbent software vendors are embedding AI into products that already sit inside the enterprise workflow, and foundation-model companies are adding enterprise features. The application companies that win will be those with proprietary data, deep workflow integration and switching costs that survive the next model release.
AI infrastructure — Databricks, Crusoe, Together AI, Lambda, CoreWeave — is where the largest cheques are being written, and where the capital structure most closely resembles project finance. These companies are building physical capacity — data centers, GPU clusters, power contracts — and their economics depend on utilisation and pricing power. The risk is overcapacity: if the AI demand curve flattens before the capacity comes online, the infrastructure layer is where the losses will be concentrated.
AI security is the most exit-driven category. Wiz’s $32 billion acquisition established a benchmark that every founder and investor in the category now references. The strategic logic is sound — enterprises need to secure AI agents and data — but the market structure favours platform vendors that can bundle security into an existing suite. Independent AI security companies will either be acquired or will need to achieve scale rapidly.
Vertical AI is the most defensible category in the near term because it sells into workflows with regulatory complexity and high switching costs. Harvey and Abridge have demonstrated that enterprises will pay for software that improves outcomes in legal and healthcare. The long-term risk is that the foundation models become good enough at domain tasks to commoditise the application layer. That risk is real but not imminent.
The venture capital race for enterprise AI is not a single race. It is four races running on different tracks, with different investors, different risk profiles and different definitions of success.
The foundation-model race is a capital-markets contest between two companies that have raised $187 billion between them. The application race is a commercial contest to prove that AI-native software can win enterprise budgets from incumbents and from the model companies themselves. The infrastructure race is a build-out contest that looks increasingly like project finance. And the security race is an exit contest, where the measure of success is the acquisition multiple rather than the standalone business.
The most important shift in 2026 is that the application layer has proven it can generate real revenue. Sierra at $150 million ARR, Harvey at $400 million ARR, Glean at $300 million+ ARR, Databricks at a $7 billion run-rate — these are not pilot projects or proofs-of-concept. They are production software businesses with enterprise customers, renewal cycles, and expansion revenue. That evidence did not exist two years ago, and it is the strongest argument that enterprise AI is not a bubble.
But the valuations are running ahead of the evidence. Cognition at 53x revenue, Sierra at roughly 105x ARR, Harvey at 39x ARR — these multiples assume years of hypergrowth and defensibility that no application company has yet demonstrated at scale. The market is pricing enterprise AI as if the winners are already determined. They are not. The incumbents — Microsoft, Salesforce, SAP, ServiceNow — are embedding AI into products that already sit inside the workflow, and they have distribution advantages that no startup can match.
The investors who will earn the best returns are not necessarily the ones writing the largest cheques. The crossover funds and sovereign wealth funds setting prices at the late stage are buying exposure to a theme, not underwriting a specific business. The venture firms that led the Series A and B rounds at Sierra, Harvey, Glean and Cognition are sitting on enormous paper gains, but they will only realise those gains if the companies can sustain growth through the next competitive phase. The corporate venture arms — Nvidia, Salesforce, GV — are making strategic bets that align with their parent companies’ commercial interests. Their returns will be measured in ecosystem position, not just in financial multiples.
The caveat worth stating plainly: this report rests on company announcements, investor disclosures and credible reporting. Revenue figures are company-reported and unaudited unless otherwise stated. Valuations are as disclosed at the time of the round and may not reflect current secondary-market pricing. The 2026 funding totals are dominated by two foundation-model rounds; stripping those out produces a very different picture of the enterprise AI market’s scale. The strategic read is defensible; the returns are not yet realised. The next 24 months will determine which of these four races produces durable businesses and which produces cautionary tales.
The CODEW Stat
43%. OpenAI’s $122 billion round accounted for roughly 43% of all venture capital deployed globally in Q1 2026. The two foundation-model companies together absorbed $187 billion — more than the entire enterprise application layer raised across every disclosed round in this report combined. That is the defining structural fact of the enterprise AI venture market: the capital is concentrated at the model layer, while the commercial traction is concentrated at the application layer. Investors are paying for the former; enterprises are buying the latter. The gap between those two facts is where the next phase of this market will be decided.
Sources & References
- PitchBook — Q3 2026 AI Report: AI VC funding surpasses $500B in 2026 (November 4, 2026) — pitchbook.com
- PitchBook — Q1 2026 AI VC Trends: $255.5B, surpassing full-year 2025 (May 12, 2026) — pitchbook.com
- EY / Irish Tech News — Global AI investment hits record $430B in H1 2026 (August 27, 2026) — irishtechnews.ie
- Anthropic — $65B Series H at $965B post-money valuation (May 28, 2026) — anthropic.com
- OpenAI — $122B at $852B post-money valuation (March 31, 2026) — multiple outlets including Yahoo Finance, DataCenter News
- Bloomberg — OpenAI finalizes $110B at $730B pre-money; Amazon $50B (February 27, 2026) — bloomberg.com
- Sierra — $950M Series E at $15.8B, $150M+ ARR (May 4, 2026) — multiples.vc, Dealroom
- Harvey — $550M at $15.5B, $400M ARR, 3,000+ customers (September 9, 2026) — harvey.ai
- Glean — $7.2B valuation, $774.5M total funding, $300M+ ARR — BenchGecko, Forge Global
- Cognition — $2B+ Series E at $48B, $900M revenue (September 2026) — multiples.vc, Bloomberg
- Decagon — $250M Series D at $4.5B (January 2026) — decagon.ai
- Writer — $1.9B valuation, $326M raised — Parsers VC
- Databricks — $5B at $190B, $7B revenue run-rate (August 13, 2026) — Bloomberg, multiples.vc
- Crusoe — $3.9B Series F at $30.9B (September 17, 2026) — crusoe.ai
- Together AI — $800M Series C at $8.3B (July 2026) — multiples.vc
- Lambda — $4B raise at $14.5B pre-money, 2027 IPO plan (October 2026) — TechCrunch, WSJ
- Scale AI — $29B valuation, Meta $14.3B for 49% (June 2025) — StockAnalysis
- CoreWeave — Nvidia investments, $2.3B debt facility led by Blackstone and Magnetar — coreweave.com
- Wiz / Google — $32B acquisition completed March 11, 2026 — CB Insights, Forbes, Salesforce Ventures
- Cyera — $600M Series G at $12B (June 2026); $400M from Goldman (September 2026) — cyera.com
- Vanta — $4.15B valuation, $300M ARR (April 2026) — Fortune
- Snyk — $7.4B valuation, $196.5M Series G — Parsers VC
- Abridge — $316M Series E extension at $5.3B (April 2026), $830M total raised — Fortune
- Nvidia NVentures — portfolio including Together AI, CoreWeave, Abridge, Legora, Databricks, Cohere — Seedtable, AI Funding
- Salesforce Ventures — portfolio including Anthropic, Together AI, Mistral, Sakana AI, Wiz — Seedtable, Salesforce Ventures
- a16z — Cognition, Databricks, Harvey, TypeSafe, Deeptune — ActuIA
Funding amounts and valuations are as disclosed by the companies or their investors at the time of the round. Revenue figures are company-reported and unaudited unless otherwise stated. Total AI venture funding figures are drawn from PitchBook, EY and Crunchbase and may use different methodologies. The $187 billion combined figure for OpenAI and Anthropic is the sum of the two disclosed primary rounds and is not an industry-wide total. Announced rounds are distinguished from completed closings where the distinction is material. This report does not provide investment advice.
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