Human Models creates a structured data layer that captures how individuals and groups think and make decisions, enabling AI systems to model users more accurately over time. This layer supports applications such as coaching, healthcare, and decision‑support tools by providing personalized, adaptive interactions, and it also helps teams share and reconcile reasoning across multiple AI agents. The platform is built collaboratively with customers to integrate directly into their products.
Funding
Funding not disclosed
Founders
Product
Problem
AI-driven products often lack a deep, continuous understanding of individual users, leading to superficial interactions that fail when nuanced, personalized support is required. Similarly, teams using multiple AI agents struggle with hidden reasoning, causing fragmented knowledge and poor collective decision‑making.
Solution
Human Models creates a structured “Human Model” layer that captures how individuals and groups think, decide, and evolve over time. By integrating this layer into existing products, AI components gain a persistent, personalized representation of each user, enabling adaptive coaching, learning, healthcare, and decision‑support experiences. For organizations, the same layer surfaces the reasoning behind AI agents across private chats, providing transparent, shared insights that align team members and improve collective intelligence. The service is delivered through a collaborative audit, design, and ongoing advisory process, ensuring the model fits the client’s workflow and can be continuously refined.
Target Audience
Primary customers are product teams building AI‑enabled coaching, learning, health, or decision‑support applications, and enterprises that rely on multiple AI agents for collaborative workflows.
Features
- Diagnostic audit to map cognitive touchpoints and identify gaps in user modeling or team AI reasoning
- Co‑development of a custom Human Model that encodes individual and group decision‑making patterns
- Prototype integration that delivers a working system and a playbook for future extensions
- Ongoing advisory seat to keep leadership informed about AI capabilities, limitations, and ethical considerations
- Structured representation that supports transparent AI reasoning, making hidden decision logic visible across team agents