Pull-based alarm intake
Alarms, problems, and incidents are pulled from ServiceNow, Splunk, and observability tools through per-user brokered connectors on a schedule or on demand — no global credential, no brittle push index.
For mid-sized companies
An operations team that never sleeps.
Intelligent Operations is an autonomous operations layer for your infrastructure — it watches your systems, assembles the evidence, diagnoses what broke and why, fixes the routine failures within policy, provisions infrastructure as code, and escalates the rest with a written root cause. The 24/7 coverage a mid-sized company can rarely afford to staff.
The operations loop
Watch, gather, diagnose, fix, report.
Each stage is a specialized bot on the swarm, coordinating over the same mesh as every other application — so the loop runs end to end, and a human is pulled in only where judgment is required.
Each stage is a specialized bot on the swarm; a human is pulled in only at step 4 when a fix needs judgment. Provisioning (Terraform / operator toolchain) runs alongside healing.
Architecture
Built on the connector runtime, like everything else.
Operations runs on the same rails as the rest of the platform: per-user brokered credentials, capability-scoped tools, a bot-owned store, and central cost capture. No global admin credential, no per-bot integration sprawl.
Operations cockpitThe view operators work from
Incident / alarm boardRCA timeline"Investigate" actionCost & ownership
Root-cause engineThree stages: prep → box-in → orchestrate
Evidence prepScope hardeningOrchestrated RCARollback plan
Evidence & topologyReason over data, not live commands
K8s pod / node / ownerCloud instance & IAMAlarm history1-hop graph topology
Pull connectorsPer-user brokered, on the runtime
ServiceNowSplunkDynatrace / DatadogPrometheus / CloudWatch
Remediation & SecOpsAct within policy
Self-healing actionsSecurity CenterReview gates
Operator toolchainBaked into the image
terraformkubectlhelmargocdvaultansible
Inside the root-cause engine
It reasons over a frozen evidence snapshot, not live commands — so the same incident yields the same, reviewable analysis every time.
The operations track
What the team actually does.
Packed root-cause engine
A three-stage engine pre-fetches the evidence, hardens the scope, then orchestrates the analysis — producing a root cause, impact, remediation, and rollback that trace back to the data behind them.
Self-healing within policy
Known-good fixes are applied automatically where safe; everything else escalates with a written cause. Heartbeats and watchdogs keep the system itself running unattended.
Terraform & the operator toolchain
The runtime image bakes in terraform, kubectl, helm, argocd, vault, and ansible, scoped per bot — so infrastructure is managed as reviewable code, not console clicks.
Security operations
Operations and SecOps share one runtime: the Security Center scans posture and triages findings into tickets, alongside the same incident and infrastructure signals.
Cost & review gates
Token and dollar cost is captured per task in a central ledger, and human approval gates sit wherever a change is risky — governed autonomy, not autonomy-and-hope.
Why mid-sized companies
The 24/7 ops bench you can't afford to staff.
A large enterprise can run a follow-the-sun SRE team. A 50-to-500-person company usually cannot — so off-hours incidents wait for someone to wake up, infrastructure drifts because changes happen by hand, and the same five failures get fixed over and over.
Intelligent Operations closes that gap: it covers the hours you don't staff, does the routine remediation for you, and leaves a written trail for the engineers you do have. It runs close to your systems — on your own infrastructure if you want, with full tenant isolation.
Put it on your stack.
If you run infrastructure without a full SRE team, this is the conversation to have. Early pilots get direct access to the engineer building it.