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CLUSTER AUGMENTED-GENERATION-RETRIEVAL · 21 ENTRIES · EARLIEST ENTRY 2026-08-13

Document Q&A with RAG

This cluster consists of web and enterprise applications that use retrieval-augmented generation to answer questions from uploaded documents, typically PDFs and DOCX files, with citations and semantic search. The dated history is too thin to read a shape from — only one dated entry exists before the index start, so the cluster's early trajectory cannot be characterized. Among traction leaders, HAHA-MLIVRAG shows the highest activity signal with 2 stars, followed by Intelligent-Research-Paper-Assistant (3 stars) and document-brain (0 stars).

Entry timeline

ENTRY TIMELINE

AUG 2026: 11SEP 2026: 9OCT 2026: 1
AUG 2026OCT 2026

Each bar is the month a member carries, which is a creation date where the source published one and a crawl date otherwise. Nothing in the index was found before 11 August 2026, and coverage broadened sharply on 14–15 August, so a bar from then on reports how much we found that month, not how much was built; an earlier bar reports how far back a member's own source dated it — not how long we have been watching.

Members by activity

Activity signals, not revenue.

Build origin · 4 hand-coded · 16 unlabelled

Operator · 11 hobby · 9 unlabelled

Two labels per entry, never collapsed into one: how it was built, and who stands behind it. Counted over the 20 listed below. Unlabelled means nothing has decided yet — not that the answer is small.

  1. 01MediRAG-Bedrock1★15 days—hobbyWeb app that answers medical questions from uploaded PDF documents using retrieval-augmented generation.
  2. 02HAHA-MLIVRAG2★1 moliveWeb app that combines machine learning and retrieval-augmented generation for interactive content creation.
  3. 03jev-webui0★21 days—hobbyLocal web app that evaluates batches of documents against typed questions using an external API and exports results.
  4. 04chatdoc-ai0★11 dayslivehobbyConversational web app that answers questions from uploaded PDF documents using retrieval-augmented generation and retains conversation context.
  5. 05RAG-technical-docs-rag0★15 daysliveQuestion-answering web app that retrieves and synthesizes answers from technical documentation using a self-correcting retrieval agent.
  6. 06hybrid-rag-assistant0★25 days—Local document question-answering app that combines semantic and keyword search with re-ranking to answer from uploaded documents and web pages.
  7. 07SourceFusion3★1 mo—hand-codedhobbyWeb search assistant that retrieves and reads top web results for a query, then streams a generated answer with cited sources.
  8. 08RAG-system0★1 moliveWeb app that performs retrieval-augmented generation to answer questions from a document collection.
  9. 09Multi-Modal-RAG-with-Interaction-UI4★2 mo—A multi-modal retrieval augmented generation application with an interactive React-based user interface for querying and generating responses.
  10. 10Local-RAG-Assistant1★1 mo—hobbyLocally run assistant that answers natural language questions about uploaded PDF documents using retrieval-augmented generation and a local language model.
  11. 11RAGVANBAN0★1 molivehobbyWeb application that retrieves and answers questions from uploaded documents using retrieval-augmented generation.
  12. 12tenbit-rag0★1 mo—hobbyDocument retrieval platform that ingests heterogeneous content and answers questions with retrieval-augmented generation across multiple tenants.
  13. 13production-rag0★1 mo—hobbyWeb application that lets users upload documents and ask questions, generating answers from the documents using retrieval-augmented generation.
  14. 14RAG0★29 days—hand-codedhobbyWeb app that lets users create projects, upload PDFs, and chat with document contents using retrieval-augmented generation.
  15. 15rag-pinecone-project0★1 mo—hobbyRetrieval-augmented generation app that answers questions from uploaded PDFs with source references.
  16. 16Document-RAG0★1 moliveWeb application that enables question-answering over uploaded documents using retrieval-augmented generation.
  17. 17PdfAnalyzer0★2 mo—hand-codedRetrieval-augmented generation app that uploads PDFs, embeds them, and lets users ask questions based on the documents.
  18. 18SmartDoc-AI-RAG-Chatbot0★2 molivehand-codedhobbyWeb app that answers questions from uploaded PDF documents using retrieval-augmented generation.
  19. 19DocQuery0★unknownliveWeb application that performs intelligent document search and retrieval-augmented generation to answer questions from uploaded documents.
  20. 20DocuMind - RAG Document Q&A0★unknownliveAI-powered web app that answers questions about documents using retrieval-augmented generation.

Ranked by traction, highest first, and paged 20 at a time — this is a window on the cluster, never the whole of it. Ties are broken by a stable id so a product cannot appear on two pages or fall between them. Browse every cluster.