AI development
AI that runs the workflow
We automate the repetitive parts of a process you already run: reading documents, sorting requests, checking images on a line, and moving the result into the system of record.
The problem
The work is waiting in inboxes, shared drives, and inspection steps that only a person can touch today. Adding headcount copies the same delay. A blanket “AI everywhere” project automates steps that were never the bottleneck.
We measure the path first. A step is a candidate when it has a repeatable input, a checkable output, and a tolerable error rate. Everything else stays with a person, with a queue so exceptions are visible.
What we deliver
A map of the manual path
Where time goes, which steps are worth automating, and which decisions should stay human.
Handling for files and images
Documents, photos, and tickets turned into structured results your systems can store.
Integration with the system of record
The result lands in the tool your team already trusts, instead of a side dashboard nobody opens.
A review queue
Low-confidence cases wait for a person, with the model’s suggestion sitting next to the original.
How we work
01
Time the current path
We follow one real item from arrival to done and write down every handoff.
02
Choose the steps
We keep the steps with a clear input and output, and leave judgment with the team.
03
Automate the middle
We build the model or rules, connect them, and show exceptions in a queue.
04
Count what changed
We track time per item and the error rate, then tune the threshold.