TL;DR: Janus battle-tests your AI agents to surface hallucinations, rule violations, and tool-call/performance failures. They run thousands of AI simulations against your chat/voice agents and offer custom evals for further model improvement.
Shivum and Jet left incoming roles at Anduril and IBM, dropped out of Carnegie Mellon ML, and moved to SF to build Janus full-time. They felt this pain first‑hand while building consumer-facing agents themselves: every new model or prompt tweak broke something in prod. They built Janus to give themselves the “crash‑test dummy” they wished existed from day-1.
A PR disaster (Air Canada chatbot inventing refund policies)
Users churning after one bad reply
Lawsuits or regulatory fines for poor compliance
Yet most teams still test agents manually by pasting prompts into playgrounds.
🤕 The Problem
Manual QA covers maybe 100 scenarios, while real users triggermillions. Generic testing platforms don’t understand your customers and can’t simulate nuanced back‑and‑forths at scale. This leaves companies with no actionable insights and blind spots that only appear after you ship.
🤝 Building or piloting an AI agent? Skip manual QA and get started in 15 minutes to see how Janus makes agent eval effortless. Click here to have a chat with the team.
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