Artificial Intelligence
We apply AI where it pays for itself, and say so plainly when it will not. A model that is right most of the time is only useful if being wrong is cheap and visible.
AI applied where it pays for itself: document and image extraction, support and email triage, classification, and internal assistants wired to your own data.
What we do
Artificial Intelligence
The work usually starts with document and image extraction, support and email triage, classification, or an internal assistant answering from your own data. Each of those has a measurable before and after, which is what makes it worth building.
We set the accuracy bar with you before the build, define what happens on a low-confidence result, and keep a human in the loop wherever a wrong answer costs money. Nothing is shipped as a black box with no fallback.
Your data stays under your control: we agree what may be sent to a model provider, what must stay inside your own infrastructure, and how long anything is retained.
Artificial Intelligence
What you get
A defined use case with the accuracy bar and the cost of being wrong written down
An evaluation set built from your real documents or tickets, not from samples
Low-confidence handling and human review built into the flow from the start
A written data-handling boundary: what leaves your infrastructure and what does not
Monitoring so quality drift is visible after launch, not discovered by a complaint
Our Expertise
Typical stack
Start with one conversation
Describe the problem and you get our reading of it, a scope and a price. If we are not the right fit, we will say so.