Machine Learning

Overview

Custom ML where it earns its keep — recommendation, forecasting, vision, and language — with the engineering rigor that keeps them accurate in production.

What we do

• Recommender systemsRanking, personalization, and discovery systems tuned for the business metric — not offline accuracy. We ship the cold-start path, the feedback loop, and the guardrails together.
• Time-series forecastingDemand, capacity, and anomaly forecasts that hold up past the training set — with the backtesting and the calibration that make the number usable, not just publishable.
• Computer visionInspection, detection, and document understanding where pixels carry the signal — built to the accuracy and throughput the line actually requires, not the lab demo.
• Model monitoringThe drift, quality, and fairness checks that tell you a model has gone stale before a customer tells you. Monitoring is part of the deliverable, not a phase III afterthought.