Agents enrich, diagnose, and propose fixes. Your people approve.
Modern IT operations drown in signals. Dozens of tools each raise their own alerts, on-call engineers triage the same incident from five consoles, and the knowledge of how it was fixed last time lives in people's heads. Our platform turns that firehose into governed, autonomous action: a unified observability layer as its eyes and ears, an AI orchestration core as its brain, and a safety-gated in-cluster agent as its hands. It runs our own operations and support practice every day. Customer zero is us.
Signals are normalized into one tenant-scoped schema. Investigation runs on demand. The remediation MVP proposes constrained fixes; execution requires human approval and leaves an audit trail.
Who it's for
One tired engineer. All of it lands on them.
Managed and in-house IT teams in regulated industries hit the same walls: fragmented visibility across tools, alert noise burying real incidents, console-hopping response that burns the first precious minutes on context-gathering, and privacy rules that forbid sending operational data to a third-party AI. The platform was engineered from day one for the two things a bank cannot compromise on: strict tenant isolation and data privacy, including the option to run the AI entirely inside your own network.
What the platform does
The engineer opens a solved case. Not a raw alert.
Every signal, one schema.
Alerts, tickets, logs, config changes, and security events from whatever your estate runs are normalized into one common event schema and resolved to your assets. The named tools are always examples: adapters are the only vendor-specific code, so your monitoring stack, your ITSM, and your chat platform are what the platform plugs into. You don't replace your tools to adopt it.
Enrichment in about a minute.
When a ticket arrives, an agent attaches the cross-system context an engineer would spend twenty minutes gathering: device state, recent config changes, related alerts, similar past incidents, the relevant documentation.
Investigation on demand.
Ask for an investigation and get back a structured report where every claim carries cited evidence and calibrated confidence. Confidence is never inflated beyond the evidence: a claim the agent can't support is a claim it doesn't make.
Remediation, proposed and gated.
The in-cluster agent diagnoses Kubernetes and OpenShift problems and proposes fixes from a constrained action vocabulary, never raw shell. A human approves; the action executes; everything is audited. Read-only by default, outbound-only, built for environments where "an agent fixed it" is only acceptable with the paper trail to prove it.
Wired into real loops.
A firewall configuration change triggers an automated audit; a dropped score opens a ticket assigned to whoever caused it.
Remediation MVP
The approval boundary
The remediation MVP diagnoses Kubernetes and OpenShift problems and proposes constrained fixes for human approval.
Kubernetes & OpenShiftRead-only by default · outbound-only
DiagnosisRead-only default · no raw shell
01
Diagnose, read-onlyThe in-cluster agent investigates Kubernetes and OpenShift problems.
02
ProposeFixes come from a constrained action vocabulary, never raw shell.
03 · Approval boundary
Human decisionA person must approve the proposed remediation before it runs.
Not approved
No remediation runs.Without approval, the proposed change does not run.
Approve
Constrained execution.Idempotency keys collapse duplicates; side-effecting calls never auto-retry.
Audited end to end · per-run trace · prompt registry · closed audit vocabulary.
The in-cluster agent diagnoses Kubernetes and OpenShift problems and proposes fixes from a constrained action vocabulary, never raw shell. Human approval is required before a proposed change runs. Without approval, the read-only default holds. Every run is audited.
The invariants
Twenty-two years of operations, enforced in code.
What operating IT taught us
What the platform enforces
What operating IT taught us
Vendors change; migrations never end
What the platform enforces
Adapters are the only vendor-specific code; one event schema is the contract
What operating IT taught us
Mis-attributed data in a shared platform is a breach
What the platform enforces
Every record carries its tenant; resolution fails closed; a prompt can only ever hold one tenant's data
What operating IT taught us
The tool that pages you must never make things worse
What the platform enforces
Read-only by default; a human gate on every write; the AI proposes, people promote
What operating IT taught us
Monitoring dies exactly when you need it most
What the platform enforces
Graceful degradation everywhere: ingest and ticketing still flow if the AI is down
What operating IT taught us
Automation that retries a side-effect doubles the incident
What the platform enforces
Idempotency keys collapse duplicates; side-effecting calls never auto-retry
What operating IT taught us
You cannot trust an AI you cannot audit
What the platform enforces
A prompt registry, a closed audit vocabulary, a per-run trace
What operating IT taught us
Regulated data won't leave the building
What the platform enforces
Pseudonymization before the wire, fail-closed; a self-hosted or air-gapped AI option removes the third party entirely
What operating IT taught us
Legacy and cloud-native coexist for years
What the platform enforces
Protocol-level adapters for legacy estates sit alongside Kubernetes-native remediation; one platform speaks both
AI is never a single point of failure.
How you start
A bounded 45-day start.
You start with a bounded proof of concept of about 45 days that delivers tangible visibility and automated ticket enrichment on your own estate. Then you grow into the autonomous capabilities on a predictable subscription, with a clear path to moving the AI onto your own hardware for maximum privacy and cost control.
The platform instantiated in your environment, adapters built for your estate, combined teams, structured knowledge transfer.
Every agent-authored change carries provenance.
Operations & Support
Agents work around the clock. Humans govern.
The platform operated as our own, 24/7, the way it already operates our own operations and support practice. Agents handle first-line volume; our engineers own escalation, judgment, and the outcome.
You choose where the approval line sits, and you move it as trust is earned.
Before we put an agent into your operations, it has run in ours, on real tickets, every day.
