Documents
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AI Knowledge Base Agent
An AI agent that turns your existing documents into a structured, searchable knowledge base: it ingests content, indexes it, surfaces relevant answers for employees and customers, and keeps you informed of what is outdated — without making legal or compliance decisions on its own.
Request an architecture review AI readiness diagnosticIn short
An AI Knowledge Base Agent solves the problem that most organisations already have: valuable knowledge locked in documents that nobody can find. It ingests PDFs, Word files, existing FAQs, policy documents and process guides; structures them into a searchable index; and surfaces the most relevant content when a question is asked. For customer-facing use it is the engine that backs a support agent. For internal use it is the system employees consult instead of asking HR or their manager. What it does not do: decide regulatory compliance on its own, tell a user that a contract is legally binding, or replace the human review of critical documents. The starting point is always an audit of what content exists, who owns it and who is allowed to see what.
Best for: Operations lead / office manager · HR or support team that answers the same questions repeatedly · Knowledge manager or documentation owner · CTO / team lead responsible for internal documentation
Typical context: Professional service firms with a large document base · Companies with high support or HR enquiry volume · Teams that have grown faster than their documentation has · Businesses with regulatory or compliance document libraries
When leadership usually needs this
Employees ask the same questions every week because the answer is buried in a PDF nobody can find.
The knowledge base exists but is out of date — everyone knows it cannot be trusted.
New employees spend their first month learning by asking people instead of reading existing documentation.
Customer support answers the same questions from a mix of tribal knowledge and guesswork.
Documents are scattered across email, Google Drive, SharePoint and personal folders.
Updating documentation is expensive, so it is never done until a problem occurs.
There is no way to know which documents are outdated or contradictory.
Multi-language teams can't easily find information in their own language.
Search returns too many results or nothing useful.
There is no audit of what information was given to whom.
What the agent actually does
- Ingests documents from approved sources (Drive, SharePoint, email, direct upload) and indexes them.
- Structures the content into a searchable knowledge base with topics, tags and ownership.
- Surfaces the most relevant content when a question is asked, with a source reference.
- Identifies content that has not been reviewed in a defined period and flags it to the owner.
- Identifies contradictory or duplicate content and surfaces it for resolution.
- Answers employee or customer questions from the indexed content within defined confidence thresholds.
- Routes questions it cannot answer confidently to a human.
- Logs what was asked, what was answered and when, for audit and quality review.
Inputs and outputs
Inputs and required data
Content sources
Google Drive / SharePoint foldersExisting FAQ documentsPolicy and process guidesEmail knowledge (where approved)
Governance rules
Access control: who can see whatReview cadence per content typeConfidence threshold for autonomous answersEscalation rules for unanswered or sensitive questions
Taxonomy
Topic structure and tagging schemaContent owner assignmentsDocument lifecycle rules (draft / current / archived)
System access
Read access to approved document sourcesIntegration with the answer delivery channel (chat, portal, widget)Write access to the knowledge index (not to source documents)
Outputs and business actions
- A structured, searchable knowledge base indexed from approved content
- Relevant answer suggestions with source references for each question
- A list of outdated or unreviewed content flagged to its owner
- Duplicate or contradictory content surfaced for resolution
- Unanswered or low-confidence questions routed to a human
- An audit log of questions, answers, sources and routing decisions
How the workflow works
1
Ingest
Approved documents are read from connected sources and indexed.
2
Structure
Content is tagged, assigned to topics and linked to its owner and lifecycle state.
3
Question received
An incoming question triggers a search of the knowledge index.
4
Retrieve
The most relevant content is retrieved, ranked by relevance and source freshness.
5
Confidence check
If confidence is above the threshold, the answer is surfaced with its source. Below threshold, it routes to a human.
6
Maintenance alerts
Outdated, unreviewed or contradictory content is flagged to its owner on a schedule.
7
Log
All queries, answers and routing decisions are recorded.
Human oversight and escalation
Automated
- Document ingestion and indexing
- Answering from approved content above the confidence threshold
- Surfacing outdated content to owners
- Logging all queries and answers
Requires human approval
- All new content additions to the knowledge base
- Changes to the confidence threshold or routing rules
- Answers to questions involving legal, compliance or employment topics
Escalation
- Low-confidence questions and sensitive topics are routed to a human — never autonomously answered below threshold.
Ownership: Content owners remain responsible for the accuracy of their documents. The agent organises and surfaces; humans author and approve.
Systems and integrations
Commonly integrated
Google DriveSharePoint / OneDriveExisting FAQ or help centre contentWeb chat or internal portal for delivery
Possible via API / webhook
Slack / Teams for internal Q&A deliveryCRM or support system for customer-facing useCustom document sources via API
Requires technical assessment
Legacy document management systemsERP-attached documentsScanned paper documents requiring OCR
Qualitative business impact
Employees find answers without asking HR, IT or their manager
Support teams answer consistently from one approved source
Outdated documentation is caught before it causes a problem
Onboarding time reduced as new employees can self-serve knowledge
A full audit trail of what information was given to whom
Actual impact depends on process quality, data quality, integration scope, user adoption and governance.
When it is not suitable
There is no existing document content to ingest — the problem is creating knowledge, not surfacing it.
Nobody owns the content — without ownership, no one updates or reviews it.
The content is highly regulated (legal, medical) and every answer requires human sign-off regardless of confidence.
The organisation has no governance on who is allowed to see what.
The expectation is that the knowledge base replaces legal, compliance or medical advice.
Risks, constraints and governance
The agent surfaces an outdated answer as current
Source freshness is part of the retrieval ranking. Periodic review alerts flag overdue content to its owner.
Confidential documents are surfaced to unauthorised users
Access control is defined per folder and content type during architecture review. The agent inherits, not bypasses, access permissions.
A user treats an answer as authoritative on a legal or compliance matter
Regulated-topic routing is defined during setup. Sensitive topics escalate to a human; the answer surface includes the source and a disclaimer.
Content quality degrades if nobody reviews it
Review cadences are defined per content type and the agent flags overdue reviews automatically.
Alternatives and simpler options
A structured FAQ page in the existing intranet
Better when: Content is simple, stable and small enough to maintain manually.
Better folder structure and search in Google Drive / SharePoint
Better when: The main problem is disorganisation rather than the inability to find content by meaning.
A native knowledge base in the helpdesk tool
Better when: The use case is purely customer-facing support and the helpdesk tool has a good native KB feature.
AI Knowledge Base Agent vs a static FAQ page
| Dimension | AI knowledge base agent | Static FAQ page |
|---|---|---|
| Query handling | Natural language, retrieves by meaning | Keyword search or manual browse |
| Content scope | Ingests many documents across sources | Manually curated list |
| Maintenance | Flags outdated content automatically | Updated when someone notices it is wrong |
| Audit trail | Every query logged with source | None |
| Best when | Large, multi-source document base | Small, stable, curated FAQ |
Implementation sequence
- Content audit — inventory of existing documents, their owners, sensitivity and lifecycle state.
- Governance design — access rules, confidence threshold, sensitive-topic routing.
- Taxonomy design — topic structure, tags, ownership assignments.
- Pilot scope — one department or content domain first.
- Ingestion and indexing — connect approved sources and run first index.
- Testing — validate retrieval quality and routing on real questions.
- Launch — go live on the pilot scope.
- Ongoing maintenance — review cycles, content owner alerts, quality monitoring.
What affects scope and price
Volume and variety of documents to ingestNumber of connected sources (Drive, SharePoint, other)Access control complexityConfidence threshold and routing logicLanguages supportedDelivery channel (internal portal, customer-facing chat, both)Reporting and audit requirements
Exact scope and price are defined after a short architecture review.
Frequently asked questions
No. It reads from your existing sources and creates a searchable layer on top of them. Source documents remain where they are.
It routes the question to a human. A defined confidence threshold determines what is answered automatically and what is escalated.
Yes, if access control is properly defined. The agent inherits the permissions of your document storage — it does not bypass them.
It monitors connected sources for new and changed documents and re-indexes them on a schedule. It also flags content that has not been reviewed in a defined period.
There is no fixed price — scope depends on document volume, sources, languages and governance complexity. Exact scope and price follow a short architecture review.
Yes, with different confidence thresholds and routing rules for each audience. The two use cases are configured separately during architecture review.
Find out what is locked in your documents
We start with a content audit: what documents exist, who owns them, and where the retrieval gap is greatest. You get a clear scope and a safe first step — no full build is assumed before the review.
Request an architecture review AI readiness diagnostic