Private AI Assistant and RAG Consulting
Private AI assistant and RAG consulting helps teams connect internal documents to AI workflows without losing control of sensitive information.
The work defines how documents are collected, chunked, embedded, filtered, cited, refreshed and permissioned. The goal is answer quality that can be checked, not a confident answer with no source trail.
If a team already pays for ChatGPT, Claude, Microsoft Copilot, Google Workspace, Notion, Slack or a workflow platform, the assistant plan should account for what those tools can already do.
A strong private assistant also needs operating rules: reindexing cadence, deleted-file handling, source freshness, feedback capture and a review path for bad answers.
This page is maintained by Jonathan R Reed for teams evaluating AI enablement, private workflows, existing-tool optimization and security-sensitive implementation decisions.
Each engagement is evaluated against practical questions: which tools and subscriptions already exist, what information must stay private, which users need access, how answers will be checked, what the workflow costs and how the team will verify that the deployed system keeps working after handoff.
The emphasis is useful delivery with clear boundaries, tested assumptions, cost-aware model routing, readable documentation and decisions that a technical owner can maintain after launch.