Simile lands $100M to model human choices with AI agents
Simile, a Stanford-linked artificial intelligence startup building simulations to predict human behavior, has raised $100 million in new funding. The round was led by Index Ventures, with participation from Bain Capital Ventures, A* and Hanabi Capital. The company also drew backing from prominent AI researchers Fei-Fei Li and Andrej Karpathy. Simile did not disclose its valuation.
From focus groups to behavioral modeling
The company says the capital will accelerate development of its core platform: a system that forecasts decisions by building simulations populated with AI agents designed to reflect real people’s preferences and trade-offs. Rather than relying solely on traditional surveys or focus groups, Simile aims to provide a data-driven way for organizations to test scenarios—such as how customers might respond to a product change or how markets may react to a corporate announcement—before committing resources.
Stanford roots and a broader ambition
Simile is led by co-founders Joon Park, Michael Bernstein, Percy Liang, and Lainie Yallen, all of whom have academic ties to Stanford University. The team’s research background informs a stated goal that goes beyond narrow prediction tools: creating a generalized framework for simulating decision-making across contexts, from retail purchasing to investor scrutiny during earnings cycles.
How the system is trained—and where it’s being tested
Over the past seven months, the startup operated quietly while building its model, interviewing hundreds of individuals about their lives, decisions, and reasoning. Those insights were combined with historical transaction records and behavioral science research to create “digital populations” that can be placed into hypothetical situations to estimate likely outcomes.
CVS Health has tested the platform for inventory and product placement decisions, according to the company. Simile also sees demand from corporate finance teams seeking to anticipate analyst questions and refine messaging ahead of earnings calls and major announcements.
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