GraphRAG Enterprise Knowledge Intelligence
A permission-aware retrieval system combines graph traversal, semantic search, and structured lookup. Bounded context assembly returns grounded answers with citations and source provenance.
GraphRAG Enterprise Knowledge Intelligence system boundary
Source connectors feed parsing and entity and relationship extraction. Knowledge graph, vector index, and structured index support hybrid retrieval before tenant and ACL filtering, context assembly, and cited generation.
GraphRAG Enterprise Knowledge Intelligence execution path
A user question becomes a retrieval plan, graph traversal and semantic and structured searches run together, permission filters remove inaccessible results, hybrid ranking selects evidence, and the agent answers with provenance.
GraphRAG Enterprise Knowledge Intelligence context movement
Context includes bounded passages, graph relationships, structured facts, source identifiers, freshness metadata, and permission decisions. Citations point back to the selected source records.
GraphRAG Enterprise Knowledge Intelligence ownership limits
The agent cannot retrieve around ACL filters, invent source permissions, alter indexes, or treat unsupported output as evidence. Restricted-source access can require review.
GraphRAG Enterprise Knowledge Intelligence enforced controls
Connector schedules, parsing rules, entity schemas, ACL enforcement, tenant filters, ranking limits, context budgets, citation formatting, and freshness checks are deterministic.
GraphRAG Enterprise Knowledge Intelligence trust boundaries
Permission filters run before retrieval results reach the agent. Tenant isolation, source-level access, retention rules, provenance, and restricted ingestion credentials protect enterprise knowledge.
GraphRAG Enterprise Knowledge Intelligence operating model
Incremental ingestion, change detection, partitioned indexes, asynchronous graph enrichment, cached plans, bounded traversal, and context limits manage freshness and cost.
GraphRAG Enterprise Knowledge Intelligence recovery paths
Failed connectors retain the last known freshness state, malformed documents enter a review queue, partial indexes do not replace valid versions, and missing evidence produces a bounded response instead of fabricated support.
GraphRAG Enterprise Knowledge Intelligence deterministic test coverage
Tests cover parser outputs, entity and relation extraction, ACL enforcement, tenant separation, graph paths, vector retrieval, structured filters, citations, and freshness updates.
GraphRAG Enterprise Knowledge Intelligence behavior evaluation
Retrieval evaluation measures relevance, relationship coverage, hybrid ranking, permission correctness, context sufficiency, citation accuracy, and grounded answer quality.
GraphRAG Enterprise Knowledge Intelligence operational evidence
Operators inspect connector health, ingestion lag, index versions, retrieval plans, filter decisions, selected evidence, citation paths, and evaluation regressions.
GraphRAG Enterprise Knowledge Intelligence deployment boundaries
Connectors, parsers, extraction workers, graph and vector stores, retrieval services, and answer runtime deploy with separated ingestion and query credentials.
GraphRAG Enterprise Knowledge Intelligence deliberate constraints
Graph enrichment adds modeling and freshness work but exposes relationships vector similarity can miss. Bounded retrieval favors traceable evidence over maximum context volume.
GraphRAG Enterprise Knowledge Intelligence claim boundary
Illustrative GraphRAG architecture only. No customer dataset, retrieval score, accuracy result, or production outcome is claimed.
Need this architecture adapted to your workflow?
DeepVention Labs can map the requirements, boundaries, integrations, evaluation, and operating model for your system.