Integration and Context Layer for AI ITSM
The integration and context layer is the product substrate that connects enterprise systems of record and turns them into actionable context for AI ITSM.
It overlaps with context-graph, but emphasizes the engineering work required to keep data fresh, permission-aware, source-attributed, and usable by workflow execution.
Inputs
- IdP and lifecycle data: Okta, Entra, SCIM, SAML/OIDC, groups, app assignments.
- HRIS data: employees, managers, start/end dates, departments, locations.
- MDM/UEM data: Intune, Jamf, Kandji, device posture, compliance status.
- ITSM data: ServiceNow, Jira Service Management, Freshservice, incidents, requests, approvals, catalog, assets.
- Developer/source-of-truth data: Backstage, NetBox, GitHub, cloud resources, ownership metadata.
- Compliance systems: Vanta, Drata, evidence status, controls, auditor requests.
Product Requirement
The layer should preserve provenance: where each fact came from, when it was observed, which source is authoritative, and whether the acting agent is allowed to use it.
Why It Matters
ai-itsm-readiness-debt is largely context debt. If Init Intelligence can create clean context as a side effect of normal usage, it can win before customers have mature ServiceNow/CSDM programs. ^[inferred]