Products · ModelOps

Every run tracked, every model accounted for

Experiment tracking, model registry, deployment and monitoring across the full model lifecycle — with managed MLflow built in.

Track

Managed MLflow logs parameters, metrics and artifacts for every experiment — no servers to run.

Register

Versioned model registry with lineage back to datasets, code and the cluster that trained it.

Deploy

One-click promotion from registry to Token Factory endpoints or your own serving stack.

Monitor

Latency, drift and quality alerts wired into your channels — catch regressions before users do.

The full lifecycle, one platform

ModelOps closes the loop with the rest of Infraeon: datasets from DataOps, training on Compute, serving on Token Factory — every artifact and metric connected by lineage.

  • Managed MLflow, no ops burden
  • Registry with dataset & code lineage
  • Deployment and monitoring built in
Diagram of the model lifecycle: experiments, registry, deploy, monitor

Start your journey today

Tell us about your workload — an engineer, not a sales bot, will get back to you within one business day.