Atla is the only eval tool that helps you automatically discover the underlying issues in your AI agents. Understand step-level errors, prioritize recurring failure patterns, and fix issues fast–before your users ever notice.
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Congrats on the launch! The step-level annotations look detailed - can it pinpoint which tool call or reasoning step failed?
Had a ton of fun building this with the team and hope you enjoy it!
Anything you like, let me know; anything you don't like, let @kaikaidai know.
Excited to launch Atla 🚀
We built it so agent teams can ship faster, more reliably. Huge shoutout to the team for the grind that got us here. Can’t wait to help make your agents better—curious how you’re debugging today and where we can support!
Congrats on the launch! Early adopter here 👴 If you like saving time, getting things done and, you know, care about the quality of your product, then this is probably for you 😄
@karolis_mariunas Thanks Karolis! 🙏 Really appreciate you being such an engaged early user - your feedback has been invaluable in shaping the product
Very exciting! Have known the Atla team for a while now and they are excellent engineers and researchers :)
Thanks Jack for the nice words!
congrats @romanengeler
really like the focus on step-level visibility. most eval tools stop at surface metrics, but catching recurring failure patterns automatically is a big deal. excited to see how this helps debug agents faster without waiting on user reports.
thanks Luigi! Yes, we want to free up builders by removing the manual work of sifting through traces for hours