Trust is created by the knowledge chain, not by the model alone.
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A company knowledge system unlocks distributed knowledge without replacing systems of record.
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RAG supports evidence-based questions; GraphRAG adds relationships and whole-dataset patterns.
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Sources, permissions, versions and validity must be addressed during ingestion and retrieval.
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Evaluation, feedback and a knowledge owner turn a prototype into a product.
Knowledge is distributed and search alone is not enough.
Relevant knowledge lives in documents, CRM, ERP, tickets and experts. Search rarely knows which version is valid or which customer context applies.
A company knowledge system connects authoritative sources and brings knowledge into the decision context instead of creating another shadow repository.
- Sources remain authoritative
- Answers cite evidence
- Permissions follow identity
- Feedback improves quality
RAG, GraphRAG and agentic retrieval answer different questions.
RAG is strong for concrete questions with specific evidence. GraphRAG models entities and relationships to support cross-document themes and dependencies.
Agentic retrieval can decompose a complex request into multiple searches, but it also increases cost, latency and potential failure modes.
- RAG: concrete evidence
- GraphRAG: relationships and themes
- Agentic retrieval: multi-part research
- Always: evaluate real questions
Permissions, validity and source quality belong together.
A relevant result must still be hidden if the user cannot access it. Old content should not rank like an approved policy.
Each knowledge domain needs explicit rules for authority, versions, contradictions and escalation.
- Carry identity and ACLs through retrieval
- Track owner and validity
- Show source and uncertainty
- Approve sensitive actions separately
A company knowledge system needs ownership and a release rhythm.
Product value appears in difficult cases: poor scans, conflicting sources, changed products and missing access.
Start with one vertical slice and scale only after retrieval, evidence and workflow work together.
- Ground truth from real questions
- Measure retrieval and usefulness
- Triage feedback
- Monitor cost, latency and incidents
Is your knowledge ready for a company knowledge system?
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Which decision should improve?
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Which sources are authoritative?
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Are owner and validity visible?
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Can permissions be inherited?
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Which questions need relationships?
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How will quality be measured?
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Who owns knowledge rules?
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