Custom AI for Your Business
Models tuned on your documents, your terms, and your domain — answers your team can trust.
A general model knows the public internet. It does not know your products, your contracts, or the way your industry uses words. We ground models on your own material so the answers come from your data — and can cite where they came from.
What it is
A general AI model knows the public internet. It does not know your products, your contracts, your processes, or the way your industry uses words. Custom AI fixes that.
We ground models on your own documents and data — through retrieval, and fine-tuning where it helps — so answers come from your material and your terms, not a generic guess.
The result is an assistant your team can trust: it answers from your knowledge, says when it does not know, and can cite where an answer came from. It can run privately, including on your own hardware.
Who it's for
- Teams answering the same questions from a large, scattered body of documents.
- Support and operations groups that need consistent, correct answers fast.
- Companies whose domain language a generic model keeps getting wrong.
What you get
- A model grounded on your documents, terms, and domain.
- Retrieval so answers are drawn from — and can cite — your own material.
- Fine-tuning where it measurably improves results.
- A private deployment option, including on your own hardware.
- An assistant that defers when it is unsure instead of inventing an answer.
How we do it
In Discover we find where wrong or slow answers cost you most. In Design we choose between retrieval and fine-tuning and define how we will measure trust. In Build & deploy we ground the model on your material and put it in front of real users. In Optimize we tune against their questions and keep the retrieval layer current as your documents change.
It follows the same four steps we use on every engagement — see the full approach.
Proven in the field
Independent examples of this approach working in the industries we serve — construction, engineering, medical engineering, manufacturing, and renewable energy. These are cited references to others' work; they show the kind of system we build for you.
- Engineering
Ground a model on your engineering knowledge — VHB built an AI coworker on Bentley's documentation to answer engineers' questions and speed civil design. Bentley Systems — VHB (opens in new tab)
- Renewable energy
Train models on your own domain data — NREL's open Sup3rCC models downscale climate data to project future wind and solar resource at high resolution. NREL — Sup3rCC (opens in new tab)
- Manufacturing
Put a copilot grounded in your plant's own automation code and engineering data on the floor — the approach behind Siemens Industrial Copilot. Siemens — Industrial Copilot (opens in new tab)
Questions, answered
Retrieval or fine-tuning?
Usually retrieval first — it is faster, cheaper, and easy to keep current. We fine-tune when the gain is real and measurable.
Will it make things up?
We build it to answer from your material and to say when it does not know, with citations back to the source. That is the point of grounding it.
Can it stay private?
Yes. It can run on your infrastructure or your own hardware, with your data kept inside your network.
How do we keep it current?
As your documents change, the retrieval layer updates. The assistant answers from the latest material without retraining.
Put custom ai for your business to work.
Describe the workflow you'd like to fix. We'll come back within one business day with a first read on what's worth doing.