Automation & Artificial Intelligence

What we do

We build the automation layer that sits between people and the systems they work with. Most of what we ship isn’t novel, it’s a classifier on a queue, a forecast on a schedule, a workflow that takes a form and routes it. The novelty is making it reliable enough to put in front of operations.

In practice

A typical engagement begins with a process that has too many humans in it and a backlog that won’t clear. We instrument the existing workflow, label a sample, and stand up a baseline model in four to six weeks. The model goes behind a queue with human-in-the-loop review. We measure precision, recall, and the time-and-motion impact on the people downstream. Once those numbers hold for a quarter, we move it to straight-through processing for the confident decisions and keep the rest in review. We’ve shipped this pattern for claims teams, KYC operations, dealer onboarding, and citizen-services intake desks.

How we know

iBoss has been delivering software since 2007, and we’ve operated production ML workloads for clients across financial services, government, and manufacturing for the last six years. Our data and ML practice runs inside our ISO 27001 management system, model artifacts, training data, and inference logs sit under the same access controls as the rest of the platform. We don’t ship models that can’t be re-trained, re-explained, and rolled back.