AI at Branta
AI applied where it moves a number you already track. Assessment, data readiness, production build, evaluation and monitoring.
Most AI pilots die between the demo and production
Usually for one of three reasons: nobody agreed what the pilot was supposed to move, the data was not in a state the use case needed, or there was no way to tell whether it was working once real traffic hit it. We deal with all three before writing the build.
Start from the measure
We agree the number the solution has to move, and the baseline it is measured against, before any model work begins.
Assess the data honestly
If the data will not support the use case, we say so and fix that first. That conversation is cheaper now than after the build.
Prove it in production
The narrowest version that demonstrates value with real traffic, with evaluation and human oversight in place from day one.
Where AI is producing real operational value
Document and data extraction
Purchase orders, invoices, claims and forms arriving as PDF, email or scans, turned into structured records with a confidence score and a review path for the ones that need a human.
Workflow automation
Removing the manual handoffs between people and systems, keeping a decision point wherever the cost of an error is high.
Assistive interfaces
Internal and customer-facing assistants grounded in your own content, so answers are traceable to a source rather than generated from nothing.
Applied prediction
Forecasting, maintenance and quality models where there is enough history to support them, and a clear statement where there is not.
We will also tell you when AI is not the answer. A reporting problem is usually a data problem, and an integration problem is almost never solved by a model.
Talk to us
Tell us what you are trying to achieve and we will help you identify the right technology path.