Optimize
your agent

E2E Agent Optimization

Watch our launch 👇🏻

SOLUTIONS

A new paradigm for optimizing AI workflows

Optimize any generic python workflow

Trainable Parameters →

Finetune is able to optimize your workflows' prompts, codes and other parameters. All you have to do is add the relevant decorators.

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Rich Generic Feedback→

Finetune can optimize your workflow using generic feedback. Provide the feedback of your choice (rewards/loss, natural language, etc...)

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End-to-End Optimization →

With Finetune your workflow self-adapts to the feedback received from its environment. No human intervention needed.

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How it works

Finetune generalizes the key technique that enabled deep learning - back-propagation. Given your agent and declared feedback, we create a DAG that represents your workflow's execution. We then back-propagate this graph and find links between the environment feedback received and the parameters to optimize. We reason over this graph and optimize your parameters accordingly. This optimization scales extremely well and we suggest running multiple iterations for improved accuracy.

TL;DR: we optimize your AI workflow so that it's ready for production 🦾

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Integrations

Use your favorite frameworks to build your agent then come to us to optimize it :)

LangGraph Flow Langflow Haystack Llama Stack Gumloop Flowise
OpenAI SDK Llama Index Langchain Haystack Crew AI Autogen Superagent

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