Enterprise AI usually fails at the integration layer: stale data, brittle syncs, and no contract between systems.
We build integrations as versioned contracts with schema validation, replay, dead-letter handling, and end-to-end tracing.
Schemas defined and validated at every boundary.
At-least-once delivery, idempotency, and replay by design.
Validation, de-duplication, and lineage before data reaches a model.
One request traced across every system it touches.
Systems, owners, and data flows are catalogued.
Schemas and SLAs agreed between producers and consumers.
Events streamed with validation and replay.
Drift detected and corrected automatically.
Freshness and failure alerting per integration.
Downstream intelligence works on current, validated records.
Alerting on freshness, not just errors.
Contracts make swapping a vendor a contained project.
Governed AI platform foundations: access control, evaluation, cost management, and deployment standards.
Operational intelligence for planning, exception management, and day-to-day decision support.
Shop-floor data, maintenance prioritisation, and back-office automation.
Asset data, field operations, and regulatory reporting support.
An illustrative event-driven integration layer connecting ERP, CRM, and AI services under explicit contracts.