Models That Know Your Business

Off-the-shelf models are trained on the breadth of the internet, which means they excel at general tasks but often fall short when precision matters. Fine-tuning closes that gap by continuing training on your proprietary data: internal documentation, support transcripts, product catalogs, compliance policies, or any domain-specific corpus that captures how your business thinks and communicates.

The result is a model that reliably uses your terminology, respects your formatting conventions, and produces outputs calibrated to your quality bar. Fine-tuned models also tend to be leaner: a smaller, specialized model can outperform a much larger general one on in-domain tasks, reducing inference latency and cost at the same time.

ProvenAI handles the full fine-tuning lifecycle: data curation and cleaning, instruction-dataset construction, supervised fine-tuning (SFT), preference alignment (RLHF / DPO), evaluation against domain benchmarks, and deployment to your infrastructure. We work with open-weight models and leading proprietary APIs alike, so you're never locked into a single provider.

Whether you're building a customer-facing assistant, an internal knowledge tool, or an automated document-processing pipeline, fine-tuning ensures the model behaves exactly as your use case demands, reliably, at scale, and with the consistency your users expect.