AI & Automation
AI in production, not in slides.
We did not start with AI. We arrived at it after more than a decade of building the systems it has to plug into, which is why our AI work reads invoices into a real ERP and scores real compliance risk instead of demonstrating well.
The model is the easy part.
Anyone can call an API. The work is the data around it: where the input comes from, what happens when the model is wrong, who reviews the exception and how the result reaches the system that acts on it. That is the part we build.
Reading what arrives in any format.
Vendor invoices in different layouts and different languages, read, validated against history and posted into the ERP, so the finance team only sees the exceptions.
Pointing attention at the right cases.
Risk based scoring that ranks cases for follow up, so limited staff work on what matters instead of on what arrived first.
Removing the work nobody should be doing.
Repetitive data entry, routing, matching and reporting, automated inside the systems people already use.
Confidence, review and a way back.
Thresholds, review queues and full logging of what the system decided and why. Automation without a review path is a liability.
From a measured process to a monitored model.
Measure
The task timed before automation.
Assess data
Can the data support the goal.
Start small
One document type, one team.
Review path
Exceptions go to a person.
Integrate
Output lands in the real system.
Watch drift
Accuracy measured after launch.
Vendor invoices in any format and in two languages are read, validated against price history and posted to the ERP. The finance team only sees the exceptions.
One team, seventeen capabilities
We design, build and run custom software: web platforms, mobile products, AI systems and cloud infrastructure.
Highlighted is where you are. The rest is on the same team.