Every week brings a new model and a new promise. The question we ask clients is simpler: what repeated task is costing you hours, and would a human accept the machine's answer most of the time?
Where it usually pays off
- Extracting structured fields from scanned or emailed documents
- Answering questions over your own policies, contracts and records
- Classifying and routing cases to the right team
- Summarising long operational text for people who don't have time to read it
Grounding beats guessing
A model that invents an answer is worse than no model at all. We ground assistants in your data, cite the source of every answer, and keep a human in the loop wherever a wrong answer would matter.
Scanned files that used to arrive as images now arrive as searchable records. That is AI doing boring work extremely well — which is the whole point.
Measure it or drop it
We define the metric before we build: hours saved, turnaround time, error rate. If a feature can't move one of those, it doesn't ship.