CLUSTER ANSWERS-QUESTIONS-CHATBOT · 75 ENTRIES · EARLIEST ENTRY 2025-01-04
PDF document Q&A chatbots
This cluster consists of chatbots that answer user questions about uploaded PDF documents by retrieving relevant passages and generating grounded, sourced responses, often with page-number citations and streaming. Before the index start, only 3 dated product entries exist, so the cluster's dated history is too thin to read a shape from -- it predates the index or its members are undated. On traction, the highest activity signals are rag-chatbot, knowbase, and ExCort, all showing 0 stars, meaning no measurable traction is evident.
Entry timeline
ENTRY TIMELINE
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 · 1 ai-built · 14 unlabelled
Operator · 10 hobby · 1 indie · 4 unlabelled
Two labels per entry, never collapsed into one: how it was built, and who stands behind it. Counted over the 15 listed below. Unlabelled means nothing has decided yet — not that the answer is small.
- 61Chat-with-documents0★1 mo—hobbyChatbot app that lets users upload PDF documents and ask questions about the content in a conversational interface.
- 62domain_rag_chatbot0★1 mo—hobbyChatbot that answers questions from uploaded PDF documents by retrieving relevant passages and citing the source page for each answer.
- 63RAG_PDF_BOOK_ASSISTANT0★1 mo—hobbyChatbot that lets users upload a PDF document and ask questions about its content through a chat interface.
- 64Pharma-Bot0★1 mo—hobbyChatbot that answers questions from pharmaceutical PDF documents with retrieval-augmented generation and preserves conversation history.
- 65Rag-Application0★1 mo—hobbyChatbot that answers questions about uploaded PDF documents by retrieving relevant passages and generating grounded responses.
- 66Dual-Mode-Agentic-RAG-Chatbot0★1 molivehobbyChatbot that answers questions by combining document search with structured data analysis and streams responses in a chat interface.
- 67RAG-based-PDF-Chatbot0★1 mo—hobbyLocal chatbot that answers questions about uploaded PDF study materials using retrieval from the documents.
- 68Whatsapp_Agent0★2 mo—hobbyWhatsApp chatbot that answers customer questions by retrieving information from uploaded PDF documents.
- 69NexusAI-Production-Agentic-AI-System-Anthropic-SDK-RAG-Streaming-Backend-0★3 mo—hobbyChatbot application that answers questions using uploaded documents through retrieval-augmented search, offering multiple personas and real-time streaming responses.
- 70ragchatbot0★2 mo—indieChatbot that answers questions from uploaded PDF documents by retrieving relevant sections and generating grounded responses with streaming.
- 71Multi-User-Full-Stack-Rag-Application0★1 yrabandoned—hobbyMulti-user web chatbot that lets people upload documents and ask questions answered using retrieval over their own content.
- 72Ai-pdf-chatbot-Langchain0★1 yrabandoned—Chatbot that answers questions about uploaded PDF documents by retrieving relevant passages and generating sourced responses.
- 73RAG-Powered-Chatbot-for-News0★1 yrabandonedliveChatbot that answers user questions about news and current events by retrieving and summarizing relevant articles.
- 74pdfquerybot0★1 yrabandoned—ai-builtChat bot that answers questions about uploaded PDF documents and extracts relevant information.
- 75RAG Assistant - Intelligent Document Chatbot0★unknownliveChatbot that lets users upload PDF and markdown documents to build a searchable knowledge base and answer questions from that content.
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.