Enterprise AI

The architecture of enterprise AI automation

Where deterministic workflow engines end and AI reasoning begins — and how to connect both to the systems where the work actually lives.

Argbit EngineeringEngineering team2026-04-0813 min read

Two engines, one system

Enterprise automation works best as a deterministic workflow engine that delegates specific steps to reasoning components. The workflow owns state, retries, timeouts and audit. The reasoning step owns interpretation.

The integration layer decides the timeline

In most engagements the schedule is set not by model work but by integration: identity, event infrastructure, record systems and the permissions surrounding them. Plan the programme accordingly.

  • Event ingress from existing messaging or queues.
  • Typed access to records, documents and warehouses.
  • Write paths with approval and reversal semantics.
  • Observability wired to the same platform the rest of engineering uses.
References

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