AI development
Practical AI features: assistants, document workflows, search and forecasting built on your data.
We add AI where it earns its place, such as summarising documents, answering questions from your knowledge base, classifying requests or forecasting demand. Guardrails, cost limits and evaluation are designed in from day one.
Why it works
Start with the use case
We define what a good answer looks like before choosing a model, so quality can be measured.
Guardrails and cost controls
Usage limits, logging and fallbacks keep behaviour predictable and bills bounded.
Your data stays yours
We agree how data is handled before building, and only send confidential content to providers you have approved.
What is included
- LLM assistants and retrieval over your documents
- Document extraction and classification
- Recommendation and forecasting models
- Evaluation sets to measure quality
- Provider-independent architecture
- Usage, cost and failure monitoring
How we work
- 01
Frame
Pick one use case, define success and collect representative examples.
- 02
Prototype
A working demo on your data within a short, fixed timebox.
- 03
Evaluate
Measure against the examples, fix failure modes, set guardrails.
- 04
Deploy
Production integration with monitoring, limits and a fallback path.
Common questions
Do you train custom models?
When a hosted model cannot meet the requirement, we train or fine-tune one. Often retrieval and prompting over a hosted model is faster and cheaper, and we will tell you which fits.
Is our data safe?
We agree data handling before building and design the system so confidential content only goes to providers you have approved.
Tell us what you are building.
Share a few details and we will reply with next steps and an honest view on scope and budget.
- 1You send a short briefTwo minutes, no finished spec needed.
- 2We reply within a working dayWith questions, or a time for a call.
- 3You get a written plan and priceScope, timeline and cost in one page.