Simile, an AI startup spun out of Stanford, has closed a $100 million Series A funding round led by Index Ventures. The round also drew backing from Bain Capital Ventures, Hanabi Capital, and a roster of AI luminaries including former Tesla AI chief Andrej Karpathy and Stanford professor Fei-Fei Li.
The company’s pitch: build foundation models that create digital twins of actual humans, simulating how people think, feel, and respond to various stimuli. Think of it as constructing a synthetic society in software, trained on real human data, that companies can use to predict behavior before it happens in the real world.
What Simile actually does
At its core, Simile is building AI-driven simulations of human behavior and societal dynamics. The platform trains on extensive datasets of real human interactions, then generates digital replicas capable of predicting emotional reactions, consumer preferences, and broader social responses.
The applications stretch across consumer analytics, marketing strategy, financial forecasting, and policy planning.
