Task tier · Knowledge

An AI agent that turns your scattered docs into answers.

It ingests the documents you already have, organises them into a searchable knowledge base, answers questions against it for your team or customers, and keeps it current by spotting gaps and stale content as things change.

What does an AI knowledge base agent do?

A knowledge base agent builds and maintains the source of truth other agents and people rely on. It ingests your existing documents (drives, wikis, PDFs, tickets), structures them into a searchable knowledge base, answers natural-language questions against it for staff or customers, and maintains it, flagging gaps from unanswered questions and stale content as your business changes. Task tier, built on Claude with retrieval. It's the foundation that powers a chatbot, a support agent, or a call answering agent.

theagency47 · Updated June 2026
The spec sheet

How the Knowledge Base Agent actually works.

Job-to-be-doneTurn scattered documents into a searchable, maintained knowledge base that answers questions
TierTask (bounded, high volume)
Underlying modelAnthropic Claude + retrieval (RAG)
TriggerOn query (answers) + scheduled ingest/freshness sweep
InputsSource docs (Drive, wiki, PDFs, tickets), access rules, taxonomy, freshness policy
Tools availableDocument ingest, vector index, search, gap detection, access control
Autonomous decisionsChunking/structuring, answer assembly, gap + staleness flagging
Escalation rulesNo supporting content → "not documented" + flag gap · Conflicting docs → surface both + flag · Restricted content → access-gated
KPIs measuredCoverage, answer rate, citation accuracy, gaps found/closed, staleness rate
Eval suite20 test cases (citation grounding, gap detection, access enforcement).
What it does

The work it takes off your team.

Ingests your docs

Pulls in drives, wikis, PDFs, and past tickets and organises them: no manual re-authoring of what you already wrote.

Answers with citations

Replies to questions from the source content and cites where each answer came from, so it's verifiable.

Finds the gaps

Tracks questions it can't answer and surfaces exactly what documentation is missing.

Flags stale content

Spots content that's aged or conflicts with newer material so the base stays trustworthy.

Access-aware

Honours who can see what: internal vs customer-facing, team-scoped: so one base serves multiple audiences safely.

Powers other agents

Acts as the grounded source for chatbots, support, and voice agents, so they all answer consistently.

Integrations

Standard integration stack.

  • Sources: Google Drive, SharePoint, Notion, Confluence, Zendesk, PDFs
  • Interface: Slack, web search panel, embedded in other agents
  • Index: managed vector store
  • Access: role-based, audience-scoped
  • Consumers: chatbot, support, call-answering agents

Custom integrations with proprietary systems are quoted as add-ons. Not sure if yours fits? Describe your stack and we'll confirm.

What it looks like in practice

A typical run.

  1. Continuously, Staff and customers ask questions and get cited answers from the latest content.
  2. On ingest, New and updated documents are pulled in, structured, and indexed automatically.
  3. Freshness sweep, Stale or conflicting content is flagged for an owner to review.
  4. Weekly, Gap report: top unanswered questions and what to document next.
FAQ

Questions about the Knowledge Base Agent.

Do I have to rewrite our documentation?

No, it works from what you already have (drives, wikis, tickets, PDFs). It structures and indexes existing content, and tells you where the real gaps are so you write only what's missing.

Can it serve both staff and customers?

Yes. Access rules let one base answer internal questions for the team and a scoped subset for customers, without leaking internal-only content.

How does it relate to the chatbot and support agents?

It's the foundation. A chatbot, support agent, or call answering agent all answer from this base, so build it once and every customer-facing agent gets smarter.

How is it delivered?

As a Spark build, or as the foundation layer in a Workforce engagement.

Build the source of truth once.

30-minute discovery call. Point us at your docs; we'll show you a searchable base and where your gaps are. Or describe your knowledge sources and we'll send back a spec.