INFRASTRUCTUREPlatform layer

Ironsight

The infrastructure layer. AI operations management: deployment, monitoring, and security for the platform and the models it runs.

Function

Private AI, run like production software.

The layer the build path underestimates. Model serving, GPU scheduling, upgrades, and security hardening are where self-hosted AI projects stall. Ironsight is that work, productized.
Deployment

Platform deployment

Installs and upgrades the full stack on your infrastructure: on-premises, private cloud, or air-gapped, with reproducible, versioned rollouts.

Serving

Model operations

Serving, scaling, and lifecycle for the models you deploy and tune: load, version, roll back, retire.

Monitoring

Full-stack monitoring

Health, capacity, latency, and cost of the AI estate on one console, from GPU utilization to per-agent run outcomes.

Security

Security operations

Hardening baselines, patching, secrets handling, and network isolation for every platform component, maintained as configuration, not folklore.

Change

Plan-approve-execute change

Infrastructure changes follow a plan-then-execute discipline with rollback paths and complete change records, inside blast-radius limits you set.

Attribution

Operator-bound actions

Operations run with the operator's own identity and privileges. Every change is attributable to a person, and every record is reconstructable.

Next step

See the ops console against a live deployment.

A briefing walks deployment, monitoring, and an end-to-end change with rollback.