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Crunchbase will abandon its roots as a historical data provider to become an AI-powered predictions engine that forecasts startup funding rounds, acquisitions and company growth trajectories.
The San Francisco-based company announced today it will relaunch its platform with AI models that can predict future business events with up to 95% accuracy, betting that artificial intelligence will fundamentally reshape how investors and companies make decisions about private markets.
“The historical data industry as we know it is dead,” said Jager McConnell, CEO of Crunchbase, in an interview with VentureBeat. “If you are a company, a data company, and all you’re dealing with is historical data…I think you’re going to find that you don’t use it as much anymore in the future.”
AI disrupts traditional market data; Crunchbase declares the old model ‘dead’
The move marks a dramatic shift for Crunchbase, which built its reputation as a crowdsourced database of startup information over 15 years. McConnell argues that traditional data providers face an existential threat from AI systems that can easily absorb and analyze historical information.
“AI companies are an existential threat for data companies, not just software companies,” McConnell said. “If you deal in historical data, once your data gets into these systems, the facts remain facts. Even data behind paywalls eventually leaks, and once it does, your value disappears because AIs can build better insights by combining it with all the data on the internet.”
Instead of focusing solely on past events, Crunchbase now leverages its massive dataset — including usage patterns from 80 million active users — to predict future business outcomes. The company’s AI analyzes thousands of signals to forecast events around fundraising, acquisitions and growth.
How Crunchbase’s AI uses 80 million users to predict the next big startup
According to Megh Gautam, Crunchbase’s chief product officer, the company’s predictions stem from a unique combination of contributed data, captured data from public sources, and anonymized user engagement patterns.
“The real magic behind our ability to predict key milestones in company lifecycles lies in our unparalleled breadth and depth of knowledge,” Gautam told VentureBeat. “We’ve built features that are generalized, not tuned to any single dataset.”
The company claims its fun …