Crunchbase’s AI can predict startup success with 95% accuracy—will it change investing?

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 fundraising predictions achieve up to 95% precision and 99% recall in backtesting — meaning it correctly identifies most companies that go on to raise funding, with few false positives. For 12-month predictions, accuracy remains in the “high 70s percent,” according to McConnell.

Beyond fundraising, Crunchbase’s AI can predict acquisitions, IPOs, company growth and even potential layoffs — though McConnell said some negative predictions won’t be displayed publicly to avoid causing harm to companies.

The future of investing: Can AI outperform human decision-making?

The strategic shift comes as investors increasingly seek predictive signals rather than historical data alone. “The problem they’re trying to tackle is, what do we do next?” Gautam said. “Our users want to be first to market.”

Looking ahead, McConnell envisions Crunchbase becoming a platform that powers AI-driven investment decisions, potentially including automated investing systems and indexes tracking private market sectors.

“I think in five years, everyone’s dead,” McConnell warned, referring to traditional data companies. “The Salesforces of the world have to figure out what their UI experience is going to be like…this thing is so fluid that in five years, a data company that’s not doing the stuff we’re talking about won’t exist.”

The transformation positions Crunchbase to compete more directly with both traditional market intelligence providers and emerging AI-powered investment platforms. The company plans to allow customers to incorporate its predictive signals into their own models while it maintains control of its valuable underlying data.

Industry analysts note that Crunchbase’s shift comes amid growing interest in using AI for investment decisions, though many investors remain skeptical of fully automated approaches. The company’s success may depend on whether it can maintain high prediction accuracy as it scales while convincing customers to trust its AI-generated insights.

McConnell emphasizes that Crunchbase aims to augment rather than replace human decision-making: “We fundamentally believe in augmentation…investments [are] pretty subjective, and your thesis has to match, and the price has to match.”

The rebranded platform launches publicly today at Crunchbase.ai, marking what McConnell calls a “precipice of just everything changing” in how investors evaluate private companies. In his view, the future belongs not to those who collect the most data, but to those who can best predict what happens next.