Service 04 — useful AI workflows on authoritative data.
AI integration
We connect authoritative data to retrieval, copilots, governed automations, and agents built around a real decision. The work starts with the source and its contract, not with a model demo looking for somewhere to land.
The work
We choose a consequential but containable decision, connect it to the smallest authoritative corpus, and define success and failure before the model enters the loop.
01
Name the user, question, action, acceptable evidence, latency, cost, and failure consequence. If the outcome cannot be evaluated, it is not ready to automate.
02
Connect to authoritative sources with declared lineage, freshness, ownership, access, and semantics. Avoid creating another export or index unless its value and synchronization boundary are explicit.
03
Implement retrieval, structured outputs, a copilot, automation, or agent with the minimum context and capabilities required for the decision.
04
Test representative and adversarial cases, enforce permissions outside the model, record evidence, monitor quality and cost, and define human escalation before production use.
What you leave with
Tangible, not theatrical
The workflow, authoritative sources, boundaries, users, capabilities, failure modes, and operating responsibilities in one written design.
Source eligibility, freshness, lineage, access, citation, abstention, and synchronization rules the AI path must satisfy.
Tests for answer quality and groundedness, plus deterministic checks governing sensitive reads, tool calls, and side effects.
A working slice with monitoring, token and latency signals, evidence, human escalation, and a clear decision about whether to expand.
The xerocopy difference
Generic AI integration copies everything into a new corpus, points a model at it, and discovers the data problem through hallucinations. xerocopy begins by reducing the corpus to what can be defended. Each retrieved fact keeps a path to an owner, and each capability sits behind a rule evaluated outside the model.
This produces smaller prompts, clearer evaluations, narrower security surfaces, and workflows whose failures can be explained. The goal is not maximum autonomy. It is the smallest system that changes a useful decision without creating a new source of truth.
The model proposes. The policy commits. The source remains the source.
Related work
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