The full lifecycle in one graph
Inferpathio connects every stage of your ML workflow: experiments that feed a versioned registry, monitored in production, with automated retraining closing the loop.
End-to-end lineage, zero gaps
Every artifact produced in your ML workflow flows through Inferpathio's event graph. Nothing is orphaned.
Experiment Tracking
Log hyperparameters, metrics, datasets, and artifact hashes to a persistent run record. Compare any two runs with a single diff view. Filter by metric threshold to identify production candidates instantly.
ExploreModel Versioning
Content-addressed storage for model weights, feature schemas, and inference configs. Every version is immutable. Rollback is a single API call. Full lineage from training data to deployed artifact is preserved.
ExploreDrift Monitoring
Continuous statistical monitoring on live inference traffic. PSI, KS-test, and custom distribution metrics evaluated against baseline. Alerts fire through Slack, PagerDuty, or webhook before SLAs break.
ExploreAuto-Retraining
Policy-based triggers that initiate training pipelines when drift, data freshness, or scheduled conditions are met. New model candidates are validated against staging before promotion. No human in the loop required.
ExplorePlugs into your stack, not the other way around
Inferpathio wraps existing training infrastructure — you don't rewrite pipelines to adopt it.
Ready to close the loop?
Connect your first model in 15 minutes on the free plan.