Normal workflow
Sources are selected, structured, retrieved, answered from, and reviewed before sensitive use.
Use case
AI Knowledge Assistant
Policies, SOPs, client context, and past decisions are scattered.
Workflow model
Normal workflow first. AI assistance only when the path breaks.
Where the workflow breaks
A question needs judgment, source conflict resolution, or policy context.
What AI prepares
Retrieve grounded context, explain uncertainty, and draft a controlled answer.
What humans approve
Policy interpretation, customer-impacting advice, and sensitive action guidance need review.
What becomes a reusable rule
Repeated questions improve source structure, answer rules, and review guidance.
Why status quo fails
Manual coordination cannot create reliable control.
Important knowledge sits in documents, chats, and individual memory.
Teams ask the same operational questions repeatedly.
Answers lack source context.
Sensitive actions need review before execution.
Workflow Layer
The workflow becomes a controlled sequence.
Structure source material, retrieve relevant context, and answer with controlled workflow guidance.
Sources selected
Knowledge structured
Question asked
Context retrieved
Answer drafted
Human review applied
Core features
What the system needs to do.
Source indexing
Controlled retrieval
Answer grounding
Escalation rules
Usage logs
Human review
Connected tools
Tools that can participate in the flow.
Google DriveSharePointNotionCRMInternal docsAI model
Expected outcome
Less dependency on one person's memory.
Implementation
Identify source material
Implementation
Define allowed answers and review gates
Implementation
Build retrieval and response flow
Implementation
Test with real team questions
Next action
Explore AI Knowledge Assistant
Tell us where this workflow currently breaks. We will map the AI assistance, approval gates, and first build path.