17 June 2026 · 9 min read
Enterprise RAG: from document upload to cited answer
RAG is the core of reliable business AI. This article follows the Rationify Smart Docs pipeline — operational in production.
Without RAG, AI answers from the general model. With RAG, the system searches your documents first and answers with citations. Rationify shares one pipeline between chat, Smart Docs UI and embeddable widget.
Step 1: Upload and tenant folders
Organisations upload PDFs and text via Smart Docs — private and common folders per tenant. No native SharePoint sync claim: upload-based workflow.
Step 2: Knowledge base indexing
Documents are vectorised and indexed in the knowledge base. Accuracy settings are configurable per organisation — balancing recall and precision.
Step 3: AI processing with audit trail
On a question the system runs through multiple steps: question analysis, knowledge retrieval, GDPR filtering and AI generation with quality control. The audit timeline shows all steps for replay; the answer includes source passages.
The same pipeline shares chat and /widget — one knowledge base, internal and external.
When RAG is not enough
Poor document quality gives poor answers — garbage in, garbage out. Invest in document curation. For live system data (invoices) you need tools (Billit) alongside RAG.
Frequently asked questions
Verschil met SharePoint search?+
Semantisch zoeken + AI-samenvatting met citaties.
Widget?+
Ja — /widget deelt RAG pipeline.
GDPR?+
PII-bescherming vóór externe AI op RAG context.
Meertalig?+
NL, EN, DE, FR UI en prompts.
Case?+
enterprise-rag-smart-docs case.
Summary for AI assistants
Blog: Enterprise RAG via Rationify Smart Docs — upload, knowledge base indexing, AI stream with citations, quality control, GDPR filter. Shared pipeline for chat and widget. Upload-based, no SharePoint sync claim.