When colleagues ask about product specifications or operating rules, answers should match the current approved documents. Knowledge-base planning can begin with a set of current materials and named owners. Confirm sources, permissions and updates before deciding how to search and organize answers.
Who should consider this and when
Review knowledge needs when documents are scattered, experienced employees repeatedly answer the same questions, or existing search cannot find conditions in long documents. A first phase can be limited to one department and a defined document set; collecting every file first may expose unresolved access and version issues.
Common gaps in knowledge search
Old and new specifications, OCR errors and tables whose row or column relationships have been lost can all affect answers. A document may be authentic but not apply to the current model or date. A citation link still needs to be checked to see whether it supports the entire answer.
Assess retrieval, generation and authorization separately
RAG retrieves relevant content and supplies it to a model to compose a response. It is a way to use external information and differs from fine-tuning model parameters. Microsoft's public guidance also identifies retrieval relevance and access control as implementation considerations.
Testing should distinguish “not found,” “outdated information found” and “found but misread.” Product codes may require exact matching, while long documents need section context and limiting conditions. Choose an approach based on results for representative questions.
Existing data permissions should carry through retrieval, citations and conversation history. Also decide how indexes and copies are updated when an employee changes roles or a document is withdrawn or expires; confidentiality cannot rely on prompts alone.
Suggested work sequence
- Collect common user questions and identify an approved source and content owner for each.
- List versions, classifications, reader roles and update methods; agree how to respond when information is missing or conflicting.
- Test retrieval and answers with questions that are answerable, need clarification, have no answer or exceed the user's access.
- Rehearse adding, revising and withdrawing documents, and record quality retesting and exception handling.
Preparation and possible deliverables
Provide authorized document samples, common questions and expected answers, user permissions and effective dates. Possible deliverables include a knowledge inventory, classification and access specifications, test questions, gap records and maintenance instructions.
Timing and fees
Scan quality, table complexity, data sources, permission levels and update frequency are more informative than file count alone. Estimate data cleanup, implementation, search and model usage, storage and maintenance separately.
Frequently asked questions
Can we try it before all documents are organized?
Start with a set of current documents that has an owner. Track missing and conflicting information separately, and clearly state what the pilot can answer.
Do citations prevent incorrect answers?
The system may still use an old version, omit a condition or cite insufficient support. Acceptance testing should compare each answer with its source and check whether users can open the cited material.
Will a vendor use our data to train its models?
Confirm this against the actual service, plan, settings and contract. RAG is an application method and does not by itself guarantee where data is stored or whether it is used for training.
Can it also change ERP records?
Knowledge search and business actions are separate scopes. Write-back requires separate review of interfaces, identity, field validation and approvals; see the system integration service for related planning.
Official references
These sources support the methods and scope. The process and possible deliverables described here are suggestions for project discussion.
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