Automation Platforms and the Modern AI Stack

Your platform choices determine reliability, governance, and delivery velocity more than model selection alone.

Reference stack layers

LayerPurposeKey questions
OrchestrationCoordinates model calls, tools, retries, and fallbacksCan we enforce policies centrally?
Workflow engineRuns deterministic business steps around AI tasksHow are approvals and exceptions handled?
Data & retrievalIndexes and retrieves governed knowledgeCan we trace source provenance?
ObservabilityMonitors quality, latency, and costDo we detect regression quickly?
Policy controlsApplies compliance, redaction, and access rulesWho can change rules and when?

Build vs buy guidance

Buy for speed when requirements are standard; build selectively for proprietary logic, strict sovereignty needs, or deep ERP/CRM process coupling.

Recommendation: standardize telemetry and policy interfaces first so tooling can evolve without replatforming core workflows.