Your

End-to-End

Collaborative

Open Source

End-to-End

Collaborative

Open Source

End-to-End

Collaborative

Open Source

End-to-End

Collaborative

Open Source

End-to-End

AI Engineer Platform

Platform for LLM Development

Agenta provides integrated tools for prompt engineering, versioning, evaluation, and observability—all in one place

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PLAYGROUND

Accelerate Prompt Engineering

Compare prompts and models across scenarios
Turn your code into a custom playground where you can tweak your app
Empower experts to engineer and deploy prompts via the web interface

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PROMPT REGISTRY

Version and Collaborate on Prompts

Track prompt versions and their outputs
Easily deploy to production and rollback
Link prompts to their evaluations and traces

Use best practices to manage your prompts throughout their lifecycle. Systematically version your prompts and move them to production with a reliable record-keeping system. Easily connect all related information—including evaluations and traces— to your prompts.

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EVALUATION

Evaluate and Analyze

Move from vibe-checks to systematic evaluation
Run evaluations directly from the web UI
Gain insights into how changes affect output quality

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OBSERVABILITY

Trace and Debug

Debug outputs and identify root causes
Identify edge cases and curate golden sets
Monitor usage and quality

Monitor usage of your application and use traces to continuously improve accuracy.
Find edge cases and use them to curate golden sets.
Debug challenging inputs and find root causes.

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NEED HELP?

Frequently
asked questions

Create robust LLM apps in record time. Focus on your core business logic and leave the rest to us.

Have a question? Contact us on slack.

Slack support

Do I need to know how to code to create LLM applications with agenta?

Can I use agenta with a self-hosted fine-tuned model such as Llama or Falcon?

How can I limit hallucinations and improve the accuracy of my LLM apps?

Is it possible to use vector embeddings and retrieval-augmented generation with Agenta?