Artificial intelligence startup Simile has secured $100 million in fresh funding. The round, led by Index Ventures, included participation from Bain Capital Ventures, A* and Hanabi Capital. Prominent AI researchers Fei-Fei Li and Andrej Karpathy also backed the company. Simile has not revealed its valuation.
The funding will be used to advance Simile’s AI technology, which predicts human behaviour by building simulations populated with AI agents that reflect real people’s preferences.
This will help companies anticipate customer purchasing decisions, prepare for analyst questions on earnings calls, forecast reactions to corporate announcements, and move beyond traditional focus groups with data-driven behavioural modelling.
Stanford roots and a vision beyond focus groups
Simile is led by co-founders Joon Park, Michael Bernstein, Percy Liang, and Lainie Yallen, all of whom have academic ties to Stanford University. Bernstein is notably a co-author of ImageNet, the landmark dataset that set a global benchmark for computer vision research.
Their academic grounding shapes Simile’s ambitions. Rather than building narrow predictive tools, the team is pursuing a broader framework designed to simulate decision-making across contexts, from consumer purchases to investor scrutiny.
Building digital populations from real lives
Simile spent the past seven months operating quietly while developing its core model. During that time, the team conducted interviews with hundreds of individuals about their lives, decisions, and personal trade-offs.
That qualitative insight was combined with historical transaction records and academic research from behavioural science journals. The result is a system trained not just on data patterns, but on how people explain their reasoning.
Instead of analysing surface-level metrics alone, Simile constructs simulations filled with AI agents that mirror the preferences and tendencies of real individuals. These digital populations can then be placed into hypothetical scenarios to forecast likely outcomes.
From store shelves to earnings calls
The company’s technology is already being tested in live business environments. CVS Health Corp. has used the platform to guide decisions about inventory and product placement in stores. By simulating how different customer segments might respond, retailers can adjust stocking strategies before committing capital.
Simile also sees strong demand from corporate finance teams. By analysing past earnings calls, research coverage, and investor behaviour, its system can anticipate the kinds of questions analysts may raise. It can even model how specific announcements might be received, offering companies a chance to refine messaging ahead of time.
For firms accustomed to traditional focus groups and surveys, this approach offers an alternative, faster, broader, and continuously adaptable.
Our thoughts
With $100 million in new funding and support from leading venture firms and respected AI researchers, Simile is positioning itself as a new kind of forecasting engine, one that seeks to model not just markets, but the human choices that drive them.
