Internal AI assistants
Internal AI knowledge base for a distributed team: permission-aware search with cited answers
This illustrative example describes an internal AI knowledge base for a distributed team whose policies, procedures and project documents are spread across shared drives and tools. The proposed assistant answers questions in natural language from documents each employee is already allowed to see, cites its sources and says when the evidence is insufficient instead of guessing.
A fictional 60-person company working remotely across three time zones. This page shows how we would design the workflow; it is not a client project and claims no results.
- Industry
- Any distributed team
- Workflow type
- Internal AI assistants
- Services involved
The business problem
Where time and enquiries get lost
Policies, onboarding guides, operating procedures, proposals and project documentation live in several shared drives and internal tools. Staff lose time looking for the latest version or ask colleagues questions that have already been answered elsewhere.
Older and superseded documents sit alongside current ones, and some content, such as HR and financial material, is restricted. A useful assistant has to return trustworthy answers, respect those restrictions and make the source easy to check.
The manual process today
- 01Search several drives and tools for the right document
- 02Ask colleagues in chat, often across time zones
- 03Rely on bookmarks or memory to find the current version
- 04Read long documents to find a single answer
- 05Report outdated content informally, if at all
Proposed workflow
How the automation would work
- Automated step
- A person reviews or acts
- 01
Sources connected (automated)
Only approved document repositories and data sources are connected.
- 02
Content indexed (automated)
Permitted content is indexed together with its access permissions and metadata.
- 03
Stale content flagged (automated)
Duplicate, expired or superseded documents are identified where possible.
- 04
Question asked (a person reviews or acts)
An employee asks a question in natural language after signing in with single sign-on.
- 05
Permitted retrieval (automated)
Relevant passages are retrieved only from documents that employee can already access.
- 06
Cited answer (automated)
The answer links to the source documents and passages it is based on.
- 07
Insufficient evidence (automated)
When sources do not support an answer, the assistant says so and points to the document owner.
- 08
Feedback collected (a person reviews or acts)
Employees flag missing, outdated or unhelpful answers.
- 09
Content owners review (a person reviews or acts)
Owners review feedback, access logs and source freshness and update documents.
In a real project, rules, tools and approval points are agreed with you during design.
Responsibilities
What AI handles, and what stays with your team
Automation and AI
- Understanding natural-language questions
- Finding relevant passages across connected repositories
- Writing concise answers with citations
- Recognising when the evidence is insufficient
- Flagging likely duplicate or superseded documents
People on your team
- Which repositories and data sources are connected
- Access policies for HR, legal, financial and customer data
- The content and accuracy of the source documents
- Interpreting policies and giving professional advice
- Retiring outdated documents and assigning owners
Systems
Systems and integrations involved
- Document repositories
- Permission-aware retrieval
- Search index or vector database
- Language model
- Single sign-on and access controls
- Source links
- Feedback and audit logging
Component types, not a fixed product list. We confirm which of your tools can be connected, and how, during discovery.
Safeguards
Security, privacy and exceptions
- Permissions are enforced at retrieval time using existing access controls, not by asking the model to avoid restricted content
- Confidential HR, legal, financial, customer and credential data is excluded or governed by explicit access policies
- Every answer cites its sources, and answers are presented as guidance to the source material, not a replacement for it
- Access and query logs are kept for audit, with retention agreed with the business
- Index syncs are monitored; a failed sync alerts the administrator so permission changes are not missed
Measurement
What we would measure
No results are claimed for this illustrative example. A baseline of search time and repeat questions would be recorded first, and answer quality would be measured on a reviewed sample.
Potential business value
- Staff find the current answer without waiting for a colleague in another time zone
- Every answer can be checked against its source
- Outdated and ownerless documents become visible
- Existing access restrictions are respected, not bypassed
- 01Time needed to find an approved answer
- 02Percentage of answers supported by relevant source passages
- 03Rate of answers judged incorrect or unsupported in a reviewed sample
- 04Search-to-success rate and employee feedback
- 05Percentage of indexed documents with an owner and review date
- 06Permission-related incidents and stale-source reports
Related services
The services behind this workflow
Custom AI Agents
Language models connected to your approved tools and data, with permissions, logging, error handling and human approval built in.
About Custom AI AgentsDocument & Data Automation
Extract fields from invoices, forms and contracts, validate them against your rules and send uncertain values to a person.
About Document & Data AutomationFAQ
Questions about this workflow
- Could someone see a document they are not allowed to access?
- The assistant retrieves only from documents the signed-in employee can already open, using the permissions from the source systems. Restricted content is not passed to the model for that user.
- What if the assistant gives a wrong answer?
- Every answer links to its sources so it can be checked, and the assistant says when it cannot find enough evidence. Employees can flag poor answers, and a sample is reviewed regularly.
- Which document tools can it connect to?
- Common shared-drive and wiki tools can usually be connected. We confirm your repositories and their permission models during the consultation before giving a fixed-price quote.
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Next step
Discuss your automation project.
Tell us how this process works in your business today. We'll map what could be automated, what should stay with your team, and how success would be measured.