Atla develops scalable oversight products that test and assess generative AI applications. We develop evaluator models that find AI mistakes at scale, and pair them with products that help developers and domain experts to make their products better in a structured and reliable manner.

​
Why evals?

LLMs only reach their full potential when they consistently produce safe and useful results. With a few lines of code, you can catch mistakes, monitor your AI’s performance, and understand critical failure modes to fix them.

If you are building generative AI, creating high-quality evals is one of the most impactful things you can do. Without evals, it can be very difficult and time-intensive to understand how different prompts and model versions might affect your use case.

In the words of OpenAI’s president Greg Brockman:

​

​
Next steps

  1. You can also get started with running your first eval here.
  2. If you want to know more, read an introduction to LLM evals here.