Atla vs DeepEval
A side-by-side comparison of Atla and DeepEval, two Eval tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
The honest brief
Atla
Built around its own Selene LLM-judge models instead of prompting a general model, then clusters and ranks agent failures so you fix the most impactful first.
- Auto-discovers and suggests fixes
- Open-weight Selene Mini available
- Python and TypeScript SDKs
- Integrates with OpenAI and LangChain
- Y Combinator-backed team
- Younger platform, small team
- Judge-model approach is opinionated
- Free tier capped at 300 calls/month
DeepEval
Write LLM evals as Pytest-style assertions and run them in CI, backed by 50+ metrics across RAG, agents, and safety.
- Assertions run in your CI pipeline
- Metrics for RAG, agents, and safety
- Bring any judge model (BYO key)
- Integrates LangChain/CrewAI/OpenAI
- LLM-as-judge adds cost
- Dashboards need paid Confident AI
- Judge metrics can be noisy