You don't rent intelligence by the token. You take an open-weight model, teach it your work with an efficient finetuning pipeline, and run it on hardware you control. Here's how.
Pick the base that fits you - Qwen, Llama, Mistral, DeepSeek, Gemma and more. It already knows how to read, reason and write; that's the heavy, expensive part, and it's freely available. You choose the size for your hardware and budget: a compact model on a single GPU, or a large one on a cluster.
Instead of retraining a whole model from scratch, we use efficient finetuning (LoRA/QLoRA adapters, plus SFT and RLVR). Your data - handbooks, codebase, tickets, records - becomes a specialized model that answers like an expert in your field.
The pipeline is reproducible and auditable, not a black box - and the raw data never leaves your machine to do it.
Train several adapters and swap them anytime. The expensive base stays put - you just change which expert is sitting on top of it.
Mix and match. Need legal help today and medical notes tomorrow? Swap the top layers. The expensive base never moves.
No adapter on top means a smart generalist. Add the right ones and it becomes a specialist in exactly your work - without forgetting everything else.
Full retraining is how the big labs do it. It's the reason their AI is something you rent.
The whole loop - and every step stays on your infrastructure.
Examples from your field - documents, code, tickets, records. We help gather, clean and structure them.
The pipeline (SFT/RLVR) turns that data into a specialized model, on your GPU or cluster. Nothing leaves your network.
Run it on your own infrastructure, offline if you want. The model is yours to keep and reuse.
See what it takes to turn your data into a model you own - at any scale.
See it for business →