OneIQ is your infrastructure-to-context engine. We lift your infrastructure details, wherever they live, into a governed context cloud, off production, where any AI you choose can reason over them.
Works with your existing stack
Natural language interface
Ask the way you would ask a colleague, from the AI you already use. OneIQ turns the question into the right query, resolves it against your real environment and answers in plain language. Nobody writes SQL.
3 hosts in production are trending toward capacity limits within 90 days, driven primarily by memory pressure on node-7. Recommended action: rebalance workloads before the next scheduled maintenance window.
See it in action
Every architectural choice in OneIQ answers the questions a security team asks before an AI pilot gets anywhere near production infrastructure.
OneIQ lifts infrastructure details into a governed context cloud, off production. Any AI you choose reasons over that, never over live systems, and nothing is installed on the endpoints or targets OneIQ reads.
Off-production reasoningEvery Agent Zone is a named, approved boundary. They are read-only, tied to a specific cluster, fleet, or infrastructure slice. An agent can't query outside its assigned zone.
Agent ZonesAsk questions the way you'd ask a colleague, from the AI you already use. OneIQ turns each question into the right query, so nobody writes SQL and the model never holds credentials.
Natural language interfaceNo raw telemetry reaches the model. OneIQ resolves each query against governed data with its own enrichment logic and returns a structured answer. Every figure traces back to source telemetry.
Answer-shaped responses01 · Off-production reasoning
OneIQ lifts your infrastructure details into a governed context cloud, so any AI you choose works from that, never from live systems. Nothing is installed on the endpoints or targets OneIQ reads, and the model never connects to them.
Trust & Compliance02 · Agent Zones
Agent zones are access boundaries you define. Each zone controls which AI agents can query which parts of your environment, what data those queries can return, and how long the zone stays active. Your team can configure zones and revoke them just as easily.
Windows and Linux workloads running in the cloud
All Linux VMs on the KVM cluster
Everything at the DR site, and nothing at production
Web tier VMs in the DMZ only
Everything the Finance organizational unit consumes, to track and report its costs
Zone definitions are fully configurable. The examples above are illustrative defaults - your team defines the exact scope of each zone during deployment.
04 · Answer-shaped responses
Without a context layer, an agent hunts through the whole environment to answer one question. OneIQ turns the natural language question into SQL and runs it for the agent, then returns a compact, computed answer. Fewer tokens spent finding it, fewer spent reasoning over it.
hosts: 4,212 records...vm_inventory: 38,904 rows...metrics.cpu.5m: [88,91,84,...]storage.luns: 1,377 entries...k8s.pods: 1,860 entries...events.raw: 96,500...... everything, unscoped ... Ungoverned and over-reaching. The model burns its budget hunting the whole environment for the one thing that matters.
Zone: "Capacity risk - Prod"at_risk_hosts: 3headroom: 11% (90d ↓)top_driver: mem on node-7recommended_action: rebalancescope: prod only · read-only Scoped, enriched, governed. Structured for reasoning, not searching.
Getting started
Four steps, at your pace. Nobody knows your infrastructure better than the team that runs it, which makes it the lowest-risk place to run your first AI project, before extending it anywhere else.
Get OneIQ Pulse context collector and install it inside your own environment.
Connect the frontier or private model you already use, so it can reason over your own infrastructure.
Ask your first question and watch OneIQ resolve it against real, live telemetry.
Define exactly what one AI agent can see: a cluster, a fleet, or a single metric.
Define your first Agent Zone and connect AI to it in under 30 minutes.