// custom AI model training
# A model trained for your task
General-purpose AI knows a little about everything. Your business needs a model that knows everything about one thing — yours.
We train purpose-built AI models for specific tasks, end to end: dataset engineering, training, evaluation and delivery. The pipeline is built and proven — it powers the AI machinist inside our own Neutral CAM. Now it can be pointed at your domain.
What you get
A model trained for your task, delivered as a standalone model you own — not a prompt bolted onto someone else’s API with your data flowing through it.
The part most people skip. We build verified training data — computed and checked, not scraped — and capture your in-house expertise so the model learns what only your people know.
Fine-tuned on dedicated hardware, measured against a held-out evaluation set before you ever see it. You get the numbers, not a demo.
Delivered to run on hardware you own — on-premises, air-gapped if you need it, no cloud dependency, no per-query costs. Your data never leaves the building.
Task-sized models train on our own hardware. Larger models train on rented data-center GPUs, billed at cost and quoted up front. Hardware is never the reason we say no.
Retraining is built into the process. As your data grows, the model grows with it — the pipeline is yours to keep using.
How it works
- 01Scope
What should the model do, and how will we measure that it does it? We define the task and the evaluation before anything trains.
- 02Data
We build the training corpus: verified generated data where correctness can be computed, plus structured capture of your domain expertise.
- 03Train + evaluate
The model trains, then proves itself against held-out tests. If it doesn’t pass, we fix the data and train again — you see honest results.
- 04Deliver
You receive the model, deployment for your environment, and the evaluation report. On your hardware or hosted — your call.
Any size of model
Most task-specific models don't need frontier-scale compute, and those train on our own dedicated hardware. When a job calls for a larger model than our hardware fits, we rent data-center GPUs for the training run — the same hardware the big labs use, paid by the hour.
Compute is billed at cost and quoted up front, before anything runs. No markup games, no surprise bills — and no request turned away because of hardware.
Have a task in mind?
Tell us what the model should do. We'll tell you honestly whether it's trainable, what data it needs, what it will cost, and how long it will take.
Start the conversation