Governed Operations System
Independent consulting · deliveredAn AI-assisted operational decision system for a small-business client, with a human committing every change.
- Canonical source of truth
- Human commits every change
Stack
- LLM orchestration
- Conversation-corpus mining
- Request routing
- Controlled structure
- Git-based tuning
For a small-business client: a governed-AI operations system, a layered private corpus surfaced through a single routed assistant that recommends actions while a human commits every change. The architecture is my IP, and client business content stays confidential.
It mines unstructured conversation history into a canonical, normalized library (voice profiles, decision rules, records), routed so the right part surfaces per request and resolved against one source of truth rather than a pile of overlapping notes. From there it produces execution-ready templates a non-technical operator can act on directly. Nothing persists or deploys autonomously: every update is a reviewed, human-committed step.
The line I hold in this kind of build: the AI augments the workflow, it does not become the source of truth. The canonical records are the authority and stay inspectable, so a wrong suggestion is a suggestion someone declines, not a fact that quietly enters the business. On the client's own numbers, the system helped convert prospects into recurring weekly engagements and cut a core workflow by roughly a third.