Fine-tuned models, RAG solutions, and custom AI systems — delivered with precision, privacy, and performance.
Domain-specific AI is a model adapted to one field — your industry, your data, your terminology — instead of a general-purpose chatbot. It answers like it works in your sector, because it was trained and evaluated on material from that sector.
Fine-tuning teaches a model your domain's language, format and judgment over weeks of curated examples. RAG (Retrieval-Augmented Generation) grounds every answer in your own up-to-date documents — internal policies, product specs, tickets. In practice we combine both: fine-tuning for style and domain knowledge, RAG for current facts and traceability.
On-prem and your-environment options are first-class where the use case requires it, RAG indexes stay inside your environment, and no client data is used to train third-party public models. Privacy is a design constraint, not an afterthought.
It depends on the surface of your data. A scoped RAG system over existing documents can be running in weeks; fine-tuning with a real evaluation loop takes longer and is scoped after a discovery pass, so you get a concrete timeline against your data — not a guess.