train
A model built for your work.
We train an open model on your work and optimize intelligence per token, second, dollar.
1how it works
Eval. Train. Run. Our team handles each step, from the first test to the rollout.
Eval
We build a benchmark from your workflow and compare models on it.
Train
If a custom model clearly does better, we train it.
Run
A/B test on your traffic, serve on high-throughput inference, on the same API.
2training loop
Proprietary RSI loop. Our model trains other models on its own.
case 1
Bithumb (digital asset exchange, Korea)
We first built Bithumb's AI research reports on a GPT-5.6 Sol multi-stage workflow. Then we post-trained an open model to write the same reports in one call with higher accuracy
| GPT-5.6 Sol workflow → trained model | change |
|---|---|
| cost | -96.5% |
| tokens | -67.3% |
| generation calls per report | about 11 → 1 |
Start with one workflow. We scope the benchmark with you.
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