Start with governance
A knowledge base is not just a document upload. Define source ownership, permitted users, update frequency and the answers the system must refuse before choosing a model.
Retrieval architecture
Dify coordinates document processing, retrieval and the model call. Keep source documents, application data and provider credentials separated and auditable.
Evaluation
Create a fixed test set containing answerable, unanswerable and permission-sensitive questions. Measure citation quality and refusal behavior before a pilot.
Production readiness
Assign owners for source updates, incident response, cost review and answer-quality monitoring.
From need to working outcome
Select a bounded pilot
Choose one department, one document set and measurable support questions rather than importing every company file.
Clean and classify source documents
Remove expired versions, identify confidential content and assign a document owner before ingestion.
Deploy Dify and configure providers
Use a protected production-minded installation, store credentials securely and keep internal services off the public network.
Build and run the evaluation set
Test citations, missing-answer behavior, permissions and prompt-injection scenarios before employee access.
Launch with monitoring and ownership
Pilot with a small user group, review failed searches and document a scheduled content-refresh process.
AI tools for this workflow
Continue with technical deployment
Deploy Dify with Docker Compose: A Production-minded Guide
Install Dify with its official Docker Compose workflow, verify the services, protect the installation screen and prepare a reverse proxy before exposing it publicly.
What to know before you start
Should every company document be indexed?
No. Start with approved, current and clearly owned documents that match a defined use case.
How do we test answer quality?
Use a repeatable question set and score correctness, citation support, refusal behavior and access control.
Does Dify include the model?
Dify orchestrates AI applications and connects to configured model providers or compatible self-hosted endpoints; model capacity must be planned separately.