Machine Learning & Predictive Systems

When your domain, latency, or cost profile is a poor fit for a general model: specialised terminology, on-prem data, sub-millisecond inference, or a prediction task with labelled history that an API cannot see.

Enough labelled or historically true examples to define the task, plus a way to get that data out of your systems. We will tell you quickly if the set is too thin to train on.

Training is half the work. We ship serving, versioning, and monitoring so the model is an API your product can call, with a rollback path when a new version is worse.

A scoped forecast, classifier, or recommender is typically weeks, not quarters, once the data is reachable. We start with a baseline you can measure against, then iterate.