Use Cases

Internal Knowledge Assistant

Let your team find the answer that already exists, with permissions respected and sources shown.

Integrations

  • Microsoft 365
  • Google Workspace
  • Telegram
  • REST API
  • Custom Systems

The task

The answer to most internal questions already exists somewhere a wiki page, a shared drive, an old thread, a policy PDF. Finding it takes longer than asking a colleague, so people ask colleagues, and senior staff become a human search index.

What it works from

  • Wiki and intranet pages
  • Document libraries in Microsoft 365 or Google Workspace
  • Policy and process documents, including PDFs
  • Existing access control lists, which are honoured rather than flattened

The automated workflow

  1. Approved sources are indexed on a schedule, keeping their original permissions attached.
  2. A question is asked in chat or in the internal tool your team already uses.
  3. Retrieval runs only across documents the asking person is allowed to see.
  4. An answer is composed from the retrieved passages, with a link to each source.
  5. Where sources conflict, the conflict is surfaced rather than silently resolved.
  6. Where nothing relevant is found, the assistant says so and offers who to ask.

Where a human stays in control

  • Document owners decide what is indexed and what is marked authoritative.
  • Permissions are enforced at query time, so the assistant cannot become a way around access control.
  • Every answer shows its sources, so the reader verifies rather than trusts.
  • Conflicting or outdated sources are flagged for a human owner to resolve.

Integrations

  • Microsoft 365

    Identity, mail, calendars and document libraries, with permissions respected rather than bypassed.

  • Google Workspace

    Sign-in, Drive, Sheets and Calendar as data sources and destinations for automated workflows.

  • Telegram

    Bot-based notifications, approvals and conversational entry points for teams that already live there.

  • REST API

    Documented, versioned and authenticated endpoints — both consuming yours and exposing ours.

  • Custom Systems

    In-house and legacy systems without a public API, reached through a documented adapter agreed with your team.

Expected effect

Described qualitatively. Actual impact depends on your volumes, data quality and process discipline.

  • Answers that exist get found, instead of being re-derived or re-asked.
  • Onboarding is faster because new staff can self-serve on the routine questions.
  • Senior staff stop functioning as a lookup service for documented information.
  • Contradictions between documents become visible, which is often the more valuable output.

Limits and what this does not do

  • It surfaces what is written down. Undocumented institutional knowledge stays undocumented, and this tends to be the awkward discovery of the first week.
  • It does not judge which of two conflicting policies is correct; it shows both and asks a person.
  • Scanned documents without a text layer need OCR, which is separate scope.

Part of the practice

AI Agents

Agents scoped to one workflow, integrated with your systems, always reviewable by a person.

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