Fatbunny Digital
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Applied AI use case / internal knowledge assistant

Give teams evidence-backed answers from the information they are allowed to use.

Permission-aware retrieval, visible sources and clear ownership when the available evidence is not enough.

An internal knowledge assistant retrieves approved sources, checks authority and freshness, and answers with evidence or routes the knowledge gap to an owner.

Delivery
knowledge work
Scope
Human-owned
Control
Measured outcome

Business workflow

Evidence-backed answer
  1. 01Employee question
  2. 02Permission boundary
  3. 03Approved sources
  4. 04Evidence check
  5. 05Knowledge owner
  6. 06Answer with sources
  7. 07Trusted next action

The operating problem

Teams lose time searching across files and messaging colleagues, while outdated or unauthorised material can look as credible as the current source.

System mechanism

Internal knowledge assistant workflow

A real operating path showing the information, decisions, systems and accountable people required to produce a useful result.

Internal knowledge assistant: Employee question to Permission boundary to Approved sources to Evidence check to Knowledge owner to Answer with sources to Trusted next action.

  1. 01
    Business inputEmployee question

    A bounded business question enters with user identity.

  2. 02
    Decision pointPermission boundary

    Role and source permissions define the searchable corpus.

  3. 03
    Retrieval engineApproved sources

    Hybrid retrieval finds relevant and current evidence.

  4. 04
    Controlled workflowEvidence check

    Source authority, freshness and coverage are evaluated.

  5. 05
    Human gateKnowledge owner

    Insufficient or conflicting evidence is routed to the responsible person.

  6. 06
    Business systemAnswer with sources

    The assistant responds only within the approved evidence boundary.

  7. 07
    Business valueTrusted next action

    The employee can act, clarify or reach the correct owner.

Fatbunny responsibility

Fatbunny maps the current workflow, information authority, decision owners, integration boundary, review states and measurable release criteria before implementing the automation.

Capabilities

  1. 01

    Current-workflow and exception mapping

  2. 02

    Retrieval and source-authority design

  3. 03

    Bounded tools and system integration

  4. 04

    Human review and outcome measurement

Delivery decisions

  1. 01

    Define the business result before selecting a model

  2. 02

    Keep deterministic rules outside probabilistic interpretation

  3. 03

    Return missing evidence and consequential action to an owner

  4. 04

    Measure the completed workflow rather than model activity

Expected outputs

  1. 01

    An agreed workflow and operating boundary

  2. 02

    A working scenario connected to approved information and systems

  3. 03

    Evaluation evidence, ownership controls and a measured next backlog

Honest limits

  1. !

    Automation cannot repair missing source information or unclear decision ownership.

  2. !

    Sensitive data and consequential actions require explicit permissions and review.

  3. !

    A convincing demonstration is not treated as production evidence.

Start with the real work

Teams lose time searching across files and messaging colleagues, while outdated or unauthorised material can look as credible as the current source.

The first release should remove a specific coordination constraint without hiding missing information or transferring accountability to a model.

Connect information, decisions and systems

The workflow may involve Identity provider, Document repositories, Policies and procedures, Knowledge owners. Each connection receives a narrow purpose, known failure behavior and a responsible owner.

Measure the business result

Useful evidence includes evidence-backed answer, faster knowledge access, visible content gaps. Model confidence and conversation volume are not substitutes for those outcomes.

Direct answers

Common questions

What does internal knowledge assistant automate?

An internal knowledge assistant retrieves approved sources, checks authority and freshness, and answers with evidence or routes the knowledge gap to an owner.

Does the AI make every decision?

No. Known rules remain deterministic, and uncertain or consequential work returns to the accountable person shown in the workflow.

Can this connect to existing business systems?

Yes, when those systems provide suitable APIs, exports, CLI operations or MCP tools with appropriately scoped access.