Tune AI to your domain.
Turn specialized data into measurable, deployable domain-specialized AI models — with validation, QLoRA fine-tuning, rigorous evaluation, and OpenAI-compatible deployment.
1
Data
Upload JSONL, validate quality, score readiness
2
Tune
QLoRA / SFT on supported open-weight models
3
Evaluate
Base vs tuned comparison on held-out benchmarks
4
Deploy
OpenAI-compatible API with versioning
Example evaluation
Every tuned model is compared against its base model. Results are honest — if tuning does not improve the benchmark, TunerAI reports that explicitly.
| Metric | Base | Tuned | Delta |
|---|---|---|---|
| Domain accuracy | 62.4% | 78.1% | +15.7 |
| Instruction following | 81.0% | 84.2% | +3.2 |
| Safety (pass rate) | 94.0% | 93.5% | −0.5 |
Illustrative layout only. Real numbers come from your held-out evaluation set after training.