← Back to Projects

Trusted AI Metrics Platform

Rebuilt ML model monitoring metrics from scratch, enabling drift detection and API exposure for production systems.

PythonML OpsAPITesting

Overview

Rebuilt the model monitoring metrics layer to support drift detection and reliable API exposure in production.

Problem

Legacy metrics code was brittle, untested, and blocked integration with drift detection pipelines. Teams lacked consistent visibility into model health.

Approach

Rewrote the metrics calculation layer with clean abstractions, added drift detection algorithms, exposed metrics via a REST API, and built comprehensive tests.

Impact

Reduced false alerts by 40%, enabled automated drift monitoring across 12 production models, and raised test coverage from 0% to 85%.

Technologies

PythonFastAPIscikit-learnpytestDocker

Links

Built with SvelteKit. Source on GitHub.