What they do
Evaluates AI agent runs step by step and suggests fixes
How close to us
4, very close
Checks only; finds agent failures from traces, which is W2 ground; developer buyer; company inactive.
Wedges
- W2 Seeing whether your AI agents actually produce direct
Who buys
- Firm size
- sme
- Buyer type
- developer
- Role
- AI engineers building agents
- UK
- not known
Their own description (from YC)
Find and fix your agent’s most critical failures in hours, not days.
Atla helps developers cut time spent on manually reviewing traces. Atla’s LLM judge evaluates your agent step-by-step, uncovers error patterns across runs, and suggests specific fixes—so you know exactly what to fix and why.
Atla supports the most popular agent frameworks teams build with, including LangChain, CrewAI, and OpenAI Agents. With real-time monitoring, automated error detection, and prompt experimentation, Atla gives teams the visibility and control needed to confidently ship agentic systems that work.
We’re a team of researchers, engineers, entrepreneurs and operational leaders. Our expertise in evals was honed through training our own purpose-built LLM Judges, Selene and Selene Mini, which are available open-source and have been downloaded 60,000+ times.
Full teardown
No full teardown yet. On the deep list.
Technical detail
- Slug
- atla
- Lens hash
- 179096c479
- Pass
- screen
- Stale
- no