ViaCatalyst
Book Audit

Enterprise Knowledge Systems

Enterprise Knowledge RAG With Access Control

A permission-aware RAG layer for policies, contracts, product documentation, support history, and internal knowledge without crossing access boundaries.

Explore How We Engage See What We Build
Challenge Context and constraints made explicit
Approach Architecture choices connected to tradeoffs
Outcome Operational gains framed in practical terms
Learning Patterns reusable across future initiatives

Enterprise context

A distributed enterprise team had more than 1.8M internal records across document drives, a helpdesk, CRM notes, product wikis, and contract repositories. Employees were losing time to manual search, but security would not approve a general LLM layer until every answer could prove which sources were retrieved and which access rules were enforced.

Challenge

The knowledge base was fragmented and inconsistent. Some sources were public to the company, some were tenant-specific, and some were restricted by role or region. The project needed useful answers, visible citations, fast retrieval, and hard permission checks before any content entered the model context.

Approach

ViaCatalyst shaped a governed RAG architecture with source connectors, metadata enrichment, permission filters, hybrid retrieval, citation-aware context assembly, and evaluation gates for answer quality and access safety.

Impact snapshot

Representative enterprise impact indicators.

The metrics are framed as anonymized program indicators and delivery targets from the case pattern, useful for understanding the scale of improvement the architecture is designed to unlock.

Search time 62% lower

Median time to locate policy or support knowledge fell from 18 minutes to under 7 minutes in pilot workflows.

Grounded answers 91%

Evaluation set answers met source coverage and citation faithfulness thresholds after reranking.

Access leaks 0/240

Restricted-record tests produced no unauthorized context exposure in the pre-launch gate.

Freshness SLA < 4 hrs

High-change sources were designed for incremental refresh windows under four hours.

Median knowledge lookup time

Lower is better

Before
18 min
After
6.8 min

Answers with usable citations

Higher is better

Before
41%
After
91%

Restricted retrieval failures

Lower is better

Before
18 cases
After
0 cases

Architecture

How the enterprise AI system is structured.

Each case pattern is framed around data boundaries, workflow controls, validation, and operating visibility.

Governed ingestion

Document, wiki, CRM, ticket, and contract sources are normalized with source IDs, ownership metadata, freshness signals, and deletion handling.

  • Incremental sync by source system
  • Chunk metadata for tenant, workspace, role, region, and record access
  • Lineage fields preserved for citations and audits

Permission-aware retrieval

Access filters run before reranking so restricted content never enters the candidate context set.

  • Hybrid keyword and vector search
  • Pre-retrieval access filters
  • Reranking and context compression after access checks

Answer validation

Responses are scored for grounding, source coverage, citation faithfulness, and refusal behavior before expansion.

  • Golden question set across 14 departments
  • Negative tests for restricted and revoked records
  • Trace review for retrieved chunks and final answers

Implementation focus

What the work clarifies.

  • Mapped source systems, document classes, access rules, retention expectations, and deletion paths.
  • Defined retrieval contracts for answer generation, citation display, freshness, refusal handling, and audit logging.
  • Created an evaluation backlog covering permissions, stale records, unsupported claims, missing-source answers, and cross-tenant leakage attempts.
  • Designed a staged rollout from security review to internal beta, department pilots, and production monitoring.

Enterprise impact

Why the pattern matters.

  • Reduced the risk of exposing restricted internal knowledge through AI answers.
  • Gave business, IT, and security teams an inspectable architecture before broad rollout.
  • Created a measurable path for improving answer quality instead of relying on prompt tuning alone.

Next step

Turn a similar challenge into a roadmap.

Start with the Two-Week Architecture Audit so data access, workflow risk, validation, and operating needs are clear before build work expands.

Book Architecture Audit Talk to ViaCatalyst