Artificial intelligence startup Simile has emerged from stealth mode with a significant funding milestone, raising $100 million in a new investment round aimed at helping businesses better predict human behaviour. The funding round was led by Index Ventures, with participation from Bain Capital Ventures, A, and Hanabi Capital*, alongside prominent AI pioneers such as Fei-Fei Li and Andrej Karpathy. While the company has not disclosed its valuation, the scale of the investment signals strong confidence in Simile’s ambitious vision to reshape how businesses anticipate consumer and market behaviour.
Simile’s core goal is to help companies forecast human decision-making patterns — from predicting what customers are likely to buy to anticipating the questions analysts might ask during corporate earnings calls. The startup believes this could transform how organisations plan, strategise, and respond to real-world uncertainties.
Credits: Bloomberg
Emerging From Stealth With a Unique Approach
Simile has spent the last seven months in stealth mode building its foundational AI model. Unlike traditional AI systems that rely solely on structured data or historical metrics, Simile’s technology is trained using interviews with hundreds of real individuals. These interviews focus on understanding people’s experiences, behavioural tendencies, and decision-making patterns.
In addition to qualitative human insights, the company fed its AI system with historic transaction data and scientific research papers on behavioural experiments. By combining human psychology with data-driven analysis, Simile is attempting to create a new class of predictive AI capable of modelling how individuals might react to specific situations.
This hybrid training approach allows the system to move beyond simple data analysis and step into the realm of behavioural simulation — a field that many experts believe could define the next wave of AI innovation.
AI Simulations That Mirror Real People
One of Simile’s standout innovations lies in its use of AI-driven simulations populated by virtual agents. These agents are designed to mimic real human preferences, motivations, and behavioural patterns. By creating such simulations, companies can test various business strategies and scenarios before implementing them in the real world.
For instance, retailers can simulate how different customer groups might respond to pricing changes, product launches, or store layouts. Similarly, corporations can model investor or public reactions to announcements, helping them refine messaging and reduce risks associated with communication strategies.
This simulation-based approach offers companies a potential alternative to traditional focus groups and surveys, which are often time-consuming, expensive, and limited in scope. Simile’s technology promises faster insights and more scalable behavioural testing.
Early Enterprise Adoption Signals Strong Demand
Simile has already begun attracting enterprise interest. CVS Health Corp. is among the early companies testing the startup’s technology. According to Simile, CVS is using the platform to guide decisions about which products to stock and how to position them in stores. Such use cases highlight the technology’s ability to influence inventory management, merchandising strategies, and customer experience planning.
Beyond retail, Simile sees strong opportunities in the corporate and financial sectors. The company believes its AI can help businesses prepare for earnings calls by predicting potential analyst questions based on historical data, research trends, and market sentiment. This capability could give corporate leadership teams a strategic advantage in high-stakes investor communications.
Additionally, Simile aims to help organisations forecast how specific announcements or policy changes might be received by stakeholders, offering insights into reputational and market risks.
Stanford Roots and AI Leadership
Simile is led by an academically strong founding team with deep connections to Stanford University. The company was co-founded by Joon Park, Michael Bernstein, Percy Liang, and Lainie Yallen, each bringing expertise in artificial intelligence, human-computer interaction, and machine learning.
Michael Bernstein stands out as a key figure, having co-authored the influential ImageNet project, widely regarded as a breakthrough that accelerated the development of modern computer vision technologies. The founders’ combined experience positions Simile at the intersection of academic research and real-world AI deployment.
Credits: Technology Networks
The Future of Behavioural Intelligence
Simile’s emergence highlights a growing trend in AI development — moving from data analysis to predictive behavioural modelling. As businesses increasingly seek personalised customer experiences and proactive decision-making tools, AI systems capable of understanding human behaviour could become highly valuable.
However, the technology also raises broader questions around ethics, privacy, and data usage, particularly when simulating real human behaviour. How companies balance innovation with responsible AI deployment will likely shape the long-term success of platforms like Simile.
With strong funding, high-profile backers, and early enterprise traction, Simile is positioning itself as a pioneer in behavioural intelligence. If successful, the startup could redefine how organisations understand and anticipate human decision-making in an increasingly complex digital economy.
