AI · Custom
Purpose-built AI for specific business problems.
When generic tools don't solve the process, we build a dedicated system - with your data, your rules and your limits.
When clients usually bring us in
- staff hunt for information across documents
- documents are reviewed by hand
- support answers the same questions repeatedly
- you need classification or data extraction
- you want AI inside the business process, not beside it
AI isn't always the right answer
If plain automation solves the process, we don't add AI because it's fashionable. We'll tell you where AI pays off and where it doesn't.
What this means for you
- Less time spent looking for information.
- Less manual retyping of data.
- Faster processing of documents and requests.
- More consistent answers from your team.
- A clear trail of where each answer came from.
Problem → solution
How we get there
Mapping
Where time is lost and what repeats.
Selection
Which cases are worth automating.
Pilot
One process, a measurable result, a capped cost.
Integration
Embedding it into existing systems.
Controls
Spend limits, logging and approval rules.
Rollout
Further processes once the effect is proven.
How we design the AI
Use case
We start by defining which decision or step the AI takes over, and where it must stop.
Data
We map sources, quality and access. Without organised data, AI cannot produce a dependable result.
Architecture
We choose the model, the retrieval approach and the point where AI plugs into the existing process.
RAG, agents, tools
The agent uses your systems through their APIs, within the permissions you define.
Keeping AI in control
Guardrails
What the AI may and may not do, when it must ask a person and when it stops the process.
Human in the loop
A person approves the sensitive steps. Each approval is logged together with the reason.
Evaluation
Regular checks on sample sets, so we notice when answer quality drifts.
Monitoring and cost
Tracking success rate, failures and cost per task, with alerts when something deviates.
Related work
FAQ
Does our data go into a public model?
No, unless we explicitly agree to it. You define the access and the boundaries.
What if the AI gets something wrong?
A person approves sensitive steps, every step is logged and can be replayed.
When is AI not the right answer?
When plain automation or a system integration solves it. We say so up front.
Related solutions
Sounds like your project?
Send us the project description, your existing system, the tender documents or the event date.