Simile Emerges from Stealth with $100 Million to Pioneer Human Behavior Prediction

In a significant development for the artificial intelligence sector, Simile, a Stanford-born startup focused on predicting human decision-making, has officially emerged from stealth mode with $100 million in fresh funding. The substantial capital injection underscores a shifting focus in the AI industry—moving beyond text generation toward complex behavioral simulation. The round was led by Index Ventures, with participation from Bain Capital Ventures, A*, and Hanabi Capital, alongside notable angel investments from AI luminaries Fei-Fei Li and Andrej Karpathy.

This massive early-stage funding highlights the immense market appetite for "agentic" AI technologies that can not only understand language but also model and anticipate human actions in real-world scenarios.

Unlocking the "Why" Behind Human Decisions

While the current wave of Generative AI has mastered the art of creating content—text, images, and code—Simile aims to solve a fundamentally different problem: predicting how humans behave. The company’s core technology revolves around creating high-fidelity simulations of people, often referred to as "generative agents." These agents are designed to model specific populations or individuals to forecast their decisions in various contexts.

According to the company, its proprietary model has been trained on a diverse and novel dataset, including deep interviews with hundreds of individuals about their lives, historical transaction data, and a vast corpus of scientific journals focused on behavioral experiments. This multi-modal approach allows Simile’s agents to go beyond statistical guessing, offering a more grounded simulation of human preference and decision-making logic.

The practical applications for this technology are vast. In the corporate sphere, Simile’s tools could allow businesses to run "virtual focus groups" at scale. Instead of surveying real people—a process that is often slow and expensive—companies could test product launches, marketing messages, or pricing strategies against a population of AI agents that statistically mirror their target demographic.

Early reports indicate that major retail players are already exploring the technology. CVS, the American healthcare and retail giant, has reportedly been testing Simile’s service to optimize decision-making regarding product stocking and display arrangements. By simulating customer foot traffic and purchasing choices, retailers can potentially reduce waste and increase conversion rates with unprecedented precision.

A Pedigree Rooted in Stanford Research

The confidence investors have placed in Simile is largely driven by its founding team, which represents a "dream team" of academic and technical talent from Stanford University. The company was co-founded by Joon Park, Michael Bernstein, Percy Liang, and Lainie Yallen.

Joon Park, a Stanford PhD, is widely recognized for his seminal paper on "Generative Agents," which demonstrated how LLM-powered agents could simulate believable social interactions in a virtual village. This research is considered a foundational text in the emerging field of agentic AI.

Michael Bernstein, a Professor of Computer Science at Stanford, brings deep historical context to the venture. He is a co-author of the original ImageNet project, the benchmark dataset that catalyzed the modern deep learning revolution in computer vision. His involvement signals that Simile is aiming for a similar foundational impact on the field of behavioral simulation.

Percy Liang, another Stanford professor and director of the Center for Research on Foundation Models (CRFM), adds significant weight to the company’s technical architecture, ensuring that the underlying models are robust, scalable, and aligned with the latest advancements in foundation model research.

Validated by Industry Titans

The investment roster reads like a Who's Who of the AI renaissance. Leading the round is Index Ventures, a firm that has consistently bet early on transformative platforms. Their leadership in this round suggests they view behavioral simulation as the next major platform shift, comparable to the rise of SaaS or mobile computing.

Perhaps even more telling is the involvement of individual investors Fei-Fei Li and Andrej Karpathy. Li, often called the "Godmother of AI" for her work on ImageNet (alongside Bernstein) and her leadership at the Stanford Institute for Human-Centered AI (HAI), has long advocated for AI that understands the human context. Her backing validates Simile's approach to "human-centered" modeling.

Karpathy, a co-founder of OpenAI and former Director of AI at Tesla, is one of the industry's most respected pragmatic thinkers. His investment suggests technical confidence in Simile’s ability to execute on the complex promise of reliable behavioral prediction, a challenge that requires moving beyond the "hallucinations" common in standard Large Language Models (LLMs).

The Strategic Shift: From Chatbots to Simulators

Simile’s ascent marks a broader trend in the venture capital landscape. As the infrastructure layer of AI (chips and foundation models) becomes saturated and dominated by Big Tech, smart capital is moving toward the application layer—specifically, applications that solve expensive, complex business problems.

Predicting human behavior is the "Holy Grail" for industries ranging from finance and retail to public policy. Traditional methods like polling, focus groups, and A/B testing are reactive and limited in scope. Simile proposes a proactive, infinite testing ground. If successful, this technology could fundamentally alter how products are designed and how markets are analyzed.

However, the technology also raises ethical questions regarding privacy and manipulation, which the company will likely need to address as it scales. By training on "interviews with hundreds of people," Simile must navigate the complexities of data consent and the potential for its agents to reinforce biases present in behavioral data.

Key Company Highlights

The following table summarizes the core details of Simile's emergence and funding:

Looking Ahead

With $100 million in the bank and a seven-month head start in stealth development, Simile is well-positioned to aggressively hire and refine its product. The company’s immediate focus will likely be on expanding its pilot programs with enterprise partners like CVS and proving that its "simulated humans" can indeed predict the unpredictable actions of real ones.

As the AI hype cycle matures, the market is looking for "System 2" thinking in AI—models that can reason, plan, and simulate outcomes rather than just generating text. Simile stands at the forefront of this next frontier, attempting to turn the chaotic variables of human psychology into a computable, predictable science.