AI · KNOWLEDGE ASSISTANT

RAG KNOWLEDGE ASSISTANT

Turn scattered docs into one intelligent, synthesized answer.

Client
A knowledge-heavy business
Platform
AI / RAG System
Stack
Python
LangChain
Vector DB
OpenAI embeddings
React
RAG Knowledge Assistant screens

Overview

Organizations struggle with fragmented documentation and inefficient knowledge retrieval — teams spend hours searching scattered documents, PDFs and wikis with no unified, intelligent way to synthesize information across sources. This RAG (retrieval-augmented generation) system fixes that: it ingests documents from across the organization and lets anyone ask a question in plain language, returning a synthesized, cited answer drawn from every relevant source instead of a list of links to dig through.

What we built

  1. Unified document ingestion
  2. Natural-language retrieval
  3. Cross-source synthesis
  4. Cited answers
  5. PDF & wiki support

Screens

RAG Knowledge Assistant: screen 1
RAG Knowledge Assistant: screen 2
RAG Knowledge Assistant: screen 3
RAG Knowledge Assistant: screen 4
RAG Knowledge Assistant: screen 5
RAG Knowledge Assistant: screen 6

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