Simulai: AI users that test your AI agents

We built Simulai because teams are shipping AI agents faster than they can test them. Right now, most people either test with a few canned prompts or wait until real users complain. That’s risky—you miss edge cases, bias issues, or conversations that just break. Simulai flips that: we spin up AI users with different personas and scenarios to stress-test your agent before launch. Instead of just saying “works on my prompt,” you actually see how your agent handles variety, breakdowns, and recovery. The output isn’t just pass/fail—it’s conversation analysis and insights that help you fix problems early. Compared to alternatives, we’re not another evals framework or a handful of benchmarks. We’re giving you synthetic users at scale—more like staging real customer interactions than running static tests. That’s the new piece. What I’m most proud of is that this launch makes testing AI agents feel like testing web apps finally did when end-to-end testing matured. It gives founders and teams a way to trust their agents before exposing them to the world.