Ground every AI answer in knowledge your business approves.
Connect policies, product information, procedures, and enterprise knowledge so GenAI responses are relevant, traceable, and easier to govern.
Give every answer a trusted information foundation
Retrieval-augmented generation connects an AI response with information retrieved from the knowledge sources included in the deployment. The goal is to answer with relevant business context rather than relying only on a model’s general knowledge.
Approved knowledge sources
Define which documents, policies, and resources the AI should use. Content ownership and access matter as much as the amount of material available.
Relevant context retrieval
Retrieve information related to the question or task. Better-organized knowledge helps the AI work with context that is useful for the request.
Governed response preparation
Design the response around the available evidence and the permitted use of that knowledge. Missing, outdated, or conflicting information needs a clear fallback.
Improve answers by improving the knowledge behind them
Bring business context into the answer
Use product guidance, approved policies, and operational information that relate to the actual question. General model knowledge is not a substitute for your organization’s current rules.
Keep knowledge accountable
Give source content an owner and a review process. An outdated document can produce an outdated answer even when retrieval works correctly.
Support customers and employees
Use the same approved foundation for customer assistance, agent support, or internal guidance where access allows. Different audiences may need different knowledge scopes.
Learn from unanswered questions
Review requests that cannot be answered reliably. Repeated gaps can show where your content needs clearer explanations or additional coverage.
Follow the work from request to result
Define the information, owner, and expected outcome at each step.
01
Ask
Identify the question and its intended audience.
02
Retrieve
Find relevant information from the permitted sources.
03
Prepare
Build the answer around the available business context.
04
Check
Apply the response rules and identify uncertainty.
05
Improve
Review unresolved questions and maintain the knowledge.
Use Cases
Put the capability to work in a real business journey
Choose the journey that matches the work your team needs to complete.
Explain policy with the right business context
A customer asks about a return or service policy. Retrieve the relevant approved guidance and explain the next step in language suited to the customer.
- Use the permitted customer-facing sources
- Keep the response aligned with the available guidance
- Hand over exceptions that need a person
Prepare troubleshooting from maintained resources
An agent needs the appropriate guide for a reported issue. Retrieve the relevant technical context and support a clear sequence of checks.
- Identify the product and issue context
- Use the current approved troubleshooting material
- Escalate when the available evidence is insufficient
Make internal guidance easier to use
An employee asks about a process or internal policy. Scope the knowledge to the audience and prepare an answer from the permitted resources.
- Use resources approved for the employee audience
- Respect the knowledge access defined for the workflow
- Route unclear policy interpretations to the owner
Questions before you get started
No. Retrieval can reduce reliance on unsupported general knowledge, but results still depend on the sources, retrieval quality, model behavior, and response controls.
A knowledge base stores and organizes information. RAG is an approach for retrieving relevant information and using it to prepare a generated response.
Knowledge provides reference information. Memory can retain the context needed for continuity in a task or interaction. The scope and retention of memory need to be defined separately.
Start with maintained, authoritative resources. Remove contradictory guidance, identify content owners, and test the questions your users actually ask.