TrainLoop recently launched!

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^{"Eliminate unwanted responses and match ideal outputs for your product."}

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‍Founded by Jackson Stokes & Mason Pierce‍

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Unreliable RAG or code generation? TrainLoop can help.

Reasoning models have been all the rage lately because they beat generic benchmarks. The problem is that your business isn’t a generic benchmark - it’s a set of specific vertical tasks like codegen, compliance, legal or healthcare. Massive companies like Google and OpenAI have internal tools to train their models, but those aren’t available to the people that need it: the developers deploying these models into production.

The founders have been personally involved on both sides: Jackson optimized the Gemini models at Google and Mason hit the limits of off shelf models while leading engineering at Second (YC W23).

So they created TrainLoop, packaging the same RL techniques big AI labs use into an accessible platform. Their process is three simple steps:

1. Data Curation: TrainLoop's lightweight SDK (just three lines of code) gathers training signals from actual usage.
2. Training: TrainLoop builds a reward model that teaches your LLM what output you prefer.
3. Inference: Deploy automatically and call your model via standard APIs.

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https://youtu.be/XhbxHOzsxRE

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Ready to Level Up Your Model?

It’s time to move past “prompt-hell” and unreliable outputs. Join TrainLoop's alpha to make your language model an expert in your business and unlock production-ready performance.

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Learn More

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^{🌐 Visit trainloop.ai to learn more.}

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^{🤝 Join TrainLoop's alpha to make your language model an expert in your business and unlock production-ready performance.}

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^{‍‍👣 Follow TrainLoop on LinkedIn & X.}

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