Primitive Labs
Primitive Labs offers Tokyo, a development platform that makes human behavior a first-class primitive of software engineering. Its Instinct product builds calibrated behavioral models from existing customer data, simulates complete web and mobile journeys to identify friction and conversion risk, and automates implementation of approved fixes. The platform is purpose-built for high-stakes consumer experiences, particularly e-commerce and retail.
- Retail Technology
- AI Agents
- Artificial Intelligence
- Data & Analytics
- Software Only
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
Software teams often ship products without a deep understanding of how users actually behave, relying on demographic stereotypes or post-launch analytics that reveal problems only after customers have experienced them. This leads to undetected friction, abandonment, and conversion losses that are expensive to fix after release.
Solution
Tokyo provides a development platform that makes human behavior a first-class primitive of software engineering. Its Instinct product builds calibrated behavioral models of customers from existing research, analytics, and customer data, then runs those models through live web and mobile experiences to simulate complete customer journeys. The platform identifies friction, abandonment, and conversion risk with behavioral evidence behind each finding, prioritizes issues by impact and customer segment, and generates specific recommendations. Instinct agents can then implement approved changes, rerun affected journeys, and verify whether customer outcomes improve—continuously detecting new issues as the experience evolves.
Target Audience
Product and engineering teams building high-stakes consumer experiences, particularly in e-commerce and retail, who need to improve product discovery, merchandising, and promotion performance.
Features
- Customer-calibrated behavioral models built from real behavioral signals, not demographic stereotypes, capturing differences in price sensitivity, trust, intent, attention, and patience
- Full journey simulation across web and mobile, capturing every click, screen, decision, and outcome, with the ability to run thousands of journeys across paths and scenarios
- Behavioral research covering journey mapping, decision-making, friction and persistence, attention and comprehension, behavioral segmentation, and counterfactual simulation
- Prioritized findings with behavioral evidence, impact scoring, and specific recommendations for what to change
- Automated implementation of approved fixes that push changes into existing development workflows, rerun affected journeys, and verify improvements
- Session replay, heatmaps, analytics, personas, and cohorts for deeper behavioral evidence