Engineers spend 70% of their time understanding code, not writing it. That’s why we built Asimov at @reflection_ai. The best-in-class code research agent, built for teams and organizations.

Code comprehension is hard. Production codebases are large with a lot of context outside of the code itself. In blind tests, Asimov's answers to complex questions were preferred 60 - 80% of the time. Asimov works because…

1] Asimov builds a single source of truth for engineering knowledge. Asimov looks at more than just code. It pulls knowledge from your codebase, your team’s messages, your project management tools, and more. Watch it trace a bug from a chat thread to the exact PR that introduced it:

2] Asimov captures team-wide tribal knowledge with memories Asimov learns from expert feedback and captures tribal knowledge stored in engineers' minds. e.g. "asimov, remember X works in Y way" Once an update is made it benefits the entire team.

3] Asimov is designed to ingest a lot of context Today agent designs fall into two categories: RAG or agentic search. Both struggle with large codebases. Asimov uses a new multi-agent design (a big reasoner with small retrievers) to ingest large codebases.