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
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 unlabelled
Operator · 1 unlabelled
Two labels per entry, never collapsed into one: how it was built, and who stands behind it. Counted over the 1 listed below. Unlabelled means nothing has decided yet — not that the answer is small.
- 21Qrate0★unknownliveWeb app that automates question paper generation from a crowd-sourced question bank.
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.