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Chronicles

The story behind the story

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Simile, which uses AI to help companies predict human behavior, including guessing items customers might buy, raised $100M led by Index and emerges from stealth

- Simile is building a lab to help predict peoples' actions  — The company is backed by Index, A* and AI pioneer Fei-Fei Li

Bloomberg Edward Ludlow

Context & Ripple Effects

Simile’s emergence gives a funded public starting point for a company focused on modeling likely human actions. Subsequent coverage sharpens that positioning: its “agentic twins” for polling and market research are presented as a product for organizations including CVS and Gallup.

The story matters because it connects customer-purchase prediction with a broader attempt to turn modeled people into an enterprise research input, rather than a single-purpose recommendation tool.

First-order effects

  • Simile gains $100 million and the backing of Index, A* and Fei-Fei Li to build its behavior-prediction lab after operating in stealth.
  • The company now has a public market position around predicting actions and purchases, creating a clearer basis for enterprise buyers and partners to assess its offering.

Second-order effects

  • Simile’s later focus on simulated respondents for polling and research puts its approach alongside established ways companies gather consumer and opinion data; prospective buyers will need to judge whether model-generated answers are useful for their decisions.
  • A product that spans purchase prediction and research could concentrate more customer-behavior workflows in one AI supplier, increasing the importance of access to relevant enterprise use cases and validation.

Third-order effects

  • If such systems prove reliable, market research may shift part of its workflow from collecting fresh responses toward testing decisions against modeled populations—while making validation of model outputs a core competitive requirement.
  • The broader structural question is whether AI products can earn durable enterprise roles by modeling human behavior, rather than merely automating discrete tasks; Simile is an early, well-funded test of that proposition.

The trend: AI startups are moving from task automation toward enterprise systems that model and forecast customer and population behavior.

Discussion

  • @hypervisible.blacksky.app @hypervisible.blacksky.app on bluesky
    “The startup said it aims to use its technology to anticipate the decisions a person might make in any given situation.  To do that, it builds simulations populated by AI agents that represent the preferences of real people.”
  • @karpathy Andrej Karpathy on x
    Congrats on the launch @simile_ai ! (and I am excited to be involved as a small angel.) Simile is working on a really interesting, imo under-explored dimension of LLMs. Usually, the LLMs you talk to have a single, specific, crafted personality. But in principle, the native,
  • @elder_plinius @elder_plinius on x
    *simulation theory intensifies*
  • @joon_s_pk Joon Sung Park on x
    Introducing Simile. Simulating human behavior is one of the most consequential and technically difficult problems of our time. We raised $100M from Index, Hanabi, A* BCV, @karpathy @drfeifei @adamdangelo @rauchg @scottbelsky among others. [video]