We’re joining forces because of a shared a frustration:

LLM-based apps are eating the world, but understanding how a model behaves when deployed to real-world users is incredibly challenging.

When these models fail, they often do so silently. If you have your LLM-based app in production and things go wrong (hallucinations, toxicity, incorrect retrieval, or security breaches), you might be the last to become aware of the problem. Meanwhile, your users suffer for days or even weeks, eroding trust and potentially leading to churn.

That's why we're building Ottic.

We want to make it dead easy for teams to check if their AI is working as it should and to find and fix any problems quickly.