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Flagship use case

Internal Knowledge and Workflow Agent

Answer source-grounded questions, summarize work, draft tasks, route approvals, and keep an auditable history.

The problem

Institutional knowledge lives in documents, wikis, chat threads, and closed tickets, and the answer to most questions depends on who happens to be online. Onboarding is slow, the same questions are answered weekly, and process gaps are discovered only when something breaks.

Our approach

We index the sources your team already uses, mirroring each system's permissions so people can only retrieve what they could already open. An agent in Slack or Teams answers questions with citations to the governing document, refuses when the answer is not in approved material, and turns recurring gaps into drafted tickets and documentation updates for a named owner to approve. Every answer and action is logged.

Minutes, not messages

Time to a sourced answer

Illustrative target for a 100-plus person team; the actual metric is agreed during the sprint and instrumented in the pilot.

Systems involved

Google Drive / SharePointNotion / ConfluenceSlack / TeamsJira / ServiceNowGitHub

Workflow

Detect, explain, evidence, route, resolve.

Nothing changes in a system of record without a named approver. Every step is logged with the evidence the approver saw.

  1. 1

    Index with permissions intact

    Drive, SharePoint, Notion, Confluence, and ticket history are indexed with access rules mirrored from the source systems, per user, not pooled.

  2. 2

    Answer with citations

    Questions in chat get answers grounded in approved material, with links to the governing document and section. Unanswerable questions are refused and logged.

  3. 3

    Summarize and draft

    The agent turns threads into summaries, decisions into documentation drafts, and recurring questions into candidate knowledge-base entries.

  4. 4

    Route work with approval

    Human approval required

    Drafted tickets, doc updates, and process fixes go to the named owner for approval before anything is created or published.

  5. 5

    Learn from the gaps

    Refused and low-confidence questions become a ranked backlog of missing documentation, so the knowledge base improves where people actually look.

Outcomes

What changes for the business.

  • Answers with sources instead of answers with seniority
  • Faster onboarding and fewer repeated questions in chat
  • A documentation backlog ranked by real demand
  • An auditable trail of what was answered, drafted, and approved

Related solutions

Put AI to work without giving up control.

A fixed-scope Opportunity Sprint: your system map, three prioritized use cases, and a pilot plan in two weeks.