Venture Capital Deal Data
Buy and sell venture capital deal data data. Valuations, round sizes, cap table structures, exit multiples — VC AI needs real deal data beyond Crunchbase.
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What Is Venture Capital Deal Data?
Venture capital deal data encompasses detailed information on funding rounds, valuations, capital structures, and exit outcomes across the startup ecosystem. This includes round sizes, valuation metrics, cap table structures, and exit multiples that go beyond public databases like Crunchbase. The VC market has experienced significant transformation, with AI-native companies and mega-rounds dominating capital flows in 2025–2026, while the market simultaneously exhibits bifurcation between well-capitalized late-stage companies and a contracting seed-stage pipeline. Professional investors, AI platforms, and market analysts rely on granular deal-level data to understand capital concentration, sector trends, and emerging investment patterns.
Market Data
$110 billion
Largest U.S. VC Deal (2026)
Source: Statista
1,300+
Unicorn Companies Globally
Source: Forbes/TrueBridge Capital
38% of all VC dollars
Top 10 U.S. VC Companies Capital Share (Sept 2025)
Source: Chronograph PE
38.4%
Venture-Backed M&A Share (2025)
Source: Forbes/TrueBridge Capital
$2.2 trillion
Broader Venture Capital Market: U.S. Private Equity Deal Value (2025)
Source: Chronograph PE
Who Uses This Data
What AI models do with it.do with it.
AI-Powered Investment Platforms
Machine learning and Bayesian models require granular deal-level data to predict valuations, assess factor hierarchies in VC funding decisions, and benchmark portfolio companies against comparable transactions.
Late-Stage Venture Firms & Mega-Fund Managers
Track mega-round valuations, cap table structures, and exit multiples to inform deployment decisions in a market where capital is increasingly concentrated among category leaders.
Secondary Market Operators
Analyze exit timelines, liquidity events, and founder optionality as companies remain private longer; support direct secondary transactions and fund-level benchmarking.
Market Researchers & Trend Analysts
Identify sector bifurcation patterns, AI capital concentration, M&A activity, and IPO window timing to advise institutional investors and strategic acquirers.
Pricing depends on the proposed terms
We do not have a verified, comparable price for your dataset. Consider the permitted uses, license term, exclusivity, provenance, coverage and quality. A seller asking price is a proposal, not an appraisal or guaranteed sale. Compare prices only when the source, date, currency, unit and license scope are known.
What Buyers Expect
What makes it valuable.valuable.
Accuracy & Currency
Deal sizes, valuations, and round timelines must be verified and updated in near-real-time to reflect rapid market changes; buyers prioritize data beyond stale public sources.
Granular Cap Table Detail
Investors expect ownership percentages, liquidation preferences, anti-dilution terms, and secondary transaction history to model downside protection and dilution scenarios.
Exit Multiples & Returns
Historical performance data linking entry valuations to exit proceeds (IPO, acquisition, secondary sales) is essential for benchmarking and return attribution analysis.
Sector & Stage Stratification
Data must clearly segment mega-rounds from seed/early-stage deals to reflect market bifurcation; buyers need confidence that statistics reflect their target universe.
Potential applications and organizations
Who's buying.buying.
Track largest deals (OpenAI $110B, Anthropic $30B), monitor capital concentration among top-10 companies, and benchmark portfolio company valuations.
Analyze late-stage unicorn valuations, exit timelines, and M&A activity to identify liquidity opportunities and structure secondary transactions.
Ingest deal-level datasets to train valuation models, predict funding outcomes, and provide benchmarking tools to portfolio companies.
Monitor capital concentration trends (38% to top 10 companies), bifurcation signals between mega-rounds and seed-stage drought, and sector rotation patterns.
FAQ
Common questions.questions.
What makes venture capital deal data valuable beyond Crunchbase?
Granular cap table structures, liquidation preferences, anti-dilution terms, and exit multiples tied to actual returns provide machine-learning models and institutional investors the precision needed to predict valuations and assess downside risk. Public databases lack these transaction-level details.
Is the VC market consolidating or fragmenting?
The market exhibits a K-shaped bifurcation: mega-rounds (e.g., OpenAI's $110B) and AI-native companies capture 38% of all U.S. VC dollars among just the top 10 firms, while seed and early-stage deal flow has contracted to multi-year lows, creating a capital concentration unprecedented in recent history.
How are exit timelines changing?
Companies like Stripe, SpaceX, and Databricks demonstrate a shift toward extended private scaling supported by deep capital pools and growing secondary markets. While IPO windows have opened slightly, founders now have more flexibility to remain private longer before liquidity events.
Which sectors dominate 2025–2026 VC deal flow?
AI and infrastructure (OpenAI, Anthropic, xAI, Databricks, Scale AI) account for the largest mega-rounds, reflecting a shift from hype cycle to core infrastructure. AI funding has dramatically reshaped capital allocation, with mega-deals disproportionately favoring market leaders.
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