OrbOps AI

System and ownership intelligence

Map the systems your teams actually operate.

Discovery AI finds services, tools, dependencies, and ownership signals across the delivery environment. Uncertain relationships remain visible and are routed to teams for validation before they influence automation.

Discovery AI Agent is one of nine specialist agents in O2 AI, the agentic operations platform from OrbOps AI.

topology.discoveryIllustrative workflow
API
Queue
Database
Worker
Owner?

Discovery path

The operating map expands, then asks for validation.

01

Discover

Find systems, tools, services, and infrastructure signals.

02

Connect

Map dependencies, ownership, and delivery relationships.

03

Validate

Ask teams to confirm uncertain or operationally important links.

discovered relationships are validated before use

Living topology

A living operating map with uncertainty exposed.

The agent connects signals from cloud, delivery, and observability systems into a readable topology. Platform teams can identify dependency paths, ownership gaps, and integration candidates without treating every discovered relationship as established fact.

System map

Create a readable view of services and infrastructure.

Dependency context

Connect delivery and runtime relationships across tools.

Ownership gaps

Surface services that need a validated accountable owner.

Autodiscovery FAQ

Questions about topology, dependencies, and ownership.

How Discovery AI builds an operating map while keeping uncertain relationships open for validation.

What is AI infrastructure autodiscovery?

AI infrastructure autodiscovery finds services, cloud resources, delivery tools, dependencies, and ownership signals across an operating environment. Discovery AI organizes those signals into a readable topology that other workflows can use. Important relationships remain proposals until the available evidence or an accountable owner validates them.

How does it find service dependencies and owners?

Discovery AI connects available cloud, delivery, repository, and observability evidence to propose how services depend on one another and who may own them. It shows the evidence behind important links and marks missing or ambiguous ownership. Platform teams can then confirm or correct the operating map.

How are incorrect relationships handled?

A discovered relationship is not treated as certain when supporting signals conflict or remain incomplete. Discovery AI marks important or uncertain links for platform-team validation and preserves corrections as operating context. This prevents an unverified topology assumption from silently influencing incident, release, cost, or provisioning decisions.

How does autodiscovery improve AIOps and DevOps workflows?

Autodiscovery supplies shared service, dependency, tool, environment, and ownership context to incident response, cost analysis, release planning, and infrastructure requests. That common map helps specialist agents reason about the same operating environment. Teams still validate the relationships that could materially influence automation or production decisions.

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