Your own model, hosted end to end.

Arkor hosts the whole loop: an OpenAI-compatible endpoint in three clicks, request logs that become training data, managed fine-tuning, and serving for the adapters you train.

Alpha · Free during the alpha

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One platform, one loop.

Everything between your app and your weights runs in one place, so using the model and improving the model are the same workflow.

A hosted endpoint in 3 clicks

An OpenAI-compatible Gemma endpoint at your-name.arkor.app, with per-deployment API keys you can revoke. Swap it in wherever your app calls a model today.

Traffic becomes training data

Requests and responses are stored as runs you can replay, inspect, and turn into a dataset. Your production traffic is the most honest training data you own.

Managed fine-tuning

Training runs execute on managed GPUs, stream metrics back to your code, and store every checkpoint. Written in TypeScript with the open-source framework.

Serve your weights

A run produces a LoRA adapter. Load it onto the base model at the same endpoint, or publish it at its own URL, and route traffic to it when you decide.

Arkor gives you control of the weights, not promises about them. The weights change only when you run a fine-tune, and every change is a checkpoint you can inspect, serve, or roll back.