AI · alternatives · 2026
24 alternatives to Quilt – Powerful RAG UI for Document QA
Hey HN! We've just launched Quilt, a robust RAG (Retrieval-Augmented Generation) UI that revolutionizes how you interact with your documents. Key features: - Multi-user setup with private/public document collections - Advanced hybrid RAG pipeline combining full-text & vector search - Smart citations with in-browser PDF preview and highlights - Fully customizable settings and prompts through the UI Making an account is free, no need to even use a strong password: this is only to ensure your documents are separate from the rest. We're keen to hear your thoughts and feedback. What features…
Quilt is a retrieval-augmented generation interface for asking questions about documents. It supports multiple users with private and public document collections, combines full-text and vector search, and provides… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Quilt – Powerful RAG UI for Document QA launched in 2024; newer entries below may have overtaken it.
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Fabric▲690Make notes, tasks, and search, directly from the terminal.
2023 · fabric.so · its alternatives →
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Transform data chaos into scientific clarity with Quilt, the AI-powered platform that accelerates research and ensures compliance for life sciences teams.
2017 · quiltdata.com · its alternatives →
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Hey there HN! We’re Antonio, Luca, and Yuhang, and we’re excited to introduce Fast GraphRAG, an open-source RAG approach that leverages knowledge graphs and the 25 years old PageRank for better information retrieval and reasoning. Building a good RAG pipeline these days takes a lot of manual optimizations. Most engineers intuitively start from naive RAG: throw everything in a vector database and hope that semantic search is powerful enough. This can work for use cases where accuracy isn’t too important and hallucinations are tolerable, but it doesn’t work for more difficult queries that…
2024 · github.com · its alternatives →
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Dabarqus▲92Add PDF chat to your LLM app in less than 9 lines of code
2024 · dabarqus.com · its alternatives →
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I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
2024 · embedding.io · its alternatives →
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Not all improvements come from adding complexity — sometimes it's about removing it. PageIndex takes a different approach to RAG. Instead of relying on vector databases or artificial chunking, it builds a hierarchical tree structure from documents and uses reasoning-based tree search to locate the most relevant sections. This mirrors how humans approach reading: navigating through sections and context rather than matching embeddings. As a result, the retrieval feels transparent, structured, and explainable. It moves RAG away from approximate "semantic vibes" and toward explicit reasoning…
2025 · github.com · its alternatives →
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The PDF parser is a rule based parser which uses text co-ordinates (boundary box), graphics and font data. The PDF parser works off text layer and also offers a OCR option to automatically use OCR if there are scanned pages in your PDFs. The OCR feature is based off a modified version of tika which uses tesseract underneath. The PDF Parser offers the following features: * Sections and subsections along with their levels. * Paragraphs - combines lines. * Links between sections and paragraphs. * Tables along with the section the tables are found in. * Lists and nested lists. * Join content…
2024 · github.com · its alternatives →
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RAG Web UI is designed to be the most straightforward way to build your own knowledge-based Q&A system. While other RAG (Retrieval-Augmented Generation) projects might be complex, we focus on making it super easy to understand and use. Why It's The Most Beginner-Friendly: Simple Document Management - Just upload your documents (PDF, DOCX, Markdown, Text) - System handles all the complex processing automatically - No need to worry about document chunking or vectorization - Documents update automatically in the background Easy-to-Use Chat Interface - Ask questions in plain language - Get…
2025 · github.com · its alternatives →
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GUI analyzer for deep-diving into PDF files. Detect malicious payloads, understand object relationships, and extract key information for threat analysis. - seekbytes/IPA
2024 · github.com · its alternatives →
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Hey HN, we’re Adi and Arnav. A few months ago, we hit a wall trying to get LLMs to answer questions over research papers and instruction manuals. Everything worked fine, until the answer lived inside an image or diagram embedded in the PDF. Even GPT‑4o flubbed it (we recently tried O3 with the same, and surprisingly it flubbed it too). Naive RAG pipelines just pulled in some text chunks and ignored the rest. We took an invention disclosure PDF (https://drive.google.com/file/d/1ySzQgbNZkC5dPLtE3pnnVL2rW_9...) containing an IRR‑vs‑frequency graph and asked GPT “From…
2025 · github.com · its alternatives →
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Got tired of wiring up vector stores, embedding models, and chunking logic every time I needed RAG. So I built piragi. from piragi import Ragi kb = Ragi(\["./docs", "./code/\*\*/\*.py", "https://api.example.com/docs"\]) answer = kb.ask("How do I deploy this?") That's the entire setup. No API keys required - runs on Ollama + sentence-transformers locally. What it does: - All formats - PDF, Word, Excel, Markdown, code, URLs, images, audio - Auto-updates - watches sources, refreshes in background, zero query latency - Citations - every answer includes sources…
Dec 2025 · pypi.org · its alternatives →
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Rag About It▲48Dive deep into AI Retrieval Augmented Generation (RAG)
2024 · ragaboutit.com · its alternatives →
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RAGstack▲111Deploy a private ChatGPT alternative hosted within your VPC
2023 · github.com · its alternatives →
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I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…
2023 · github.com · its alternatives →
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I've been presenting at local meetups about Context Engineering, RAG, Skills, etc.. I even have a vbrownbag coming up on LinkedIn about this topic so I figured I would make a basic example that uses bedrock so I can use it in my talks or vbrownbags. Hopefully it's useful.
Apr 2026 · github.com · its alternatives →
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LiquidIndex 2.0▲134I'm building LiquidIndex, an RAG API service that makes it easy to add personalized context to AI apps. Instead of building a whole system to upload, process, and search through a user’s files or notes, you just call a few APIs. It handles the hard parts - like connecting to Notion or Google Drive, breaking the data into usable pieces, and making it searchable. Then, when you want to answer a question using that data, you just query it, and it gives you the most relevant results - optionally with an LLM-generated answer. No pipelines, no infrastructure, no headaches. Here are the core APIs:…
2025 · liquidindex.dev · its alternatives →
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RAGLite is a Python package for building Retrieval-Augmented Generation (RAG) applications. RAG applications can be magical when they work well, but anyone who has built one knows how much the output quality depends on the quality of retrieval and augmentation. With RAGLite, we set out to unhobble RAG by mapping out all of its subproblems and implementing the best solutions to those subproblems. For example, RAGLite solves the chunking problem by partitioning documents in provably optimal level 4 semantic chunks. Another unique contribution is its optimal closed-form linear query adapter…
2024 · github.com · its alternatives →
- 20IB
Hey all! I wanted to share this project I've been working on that can maybe help you or your developer friends out. I built a RAG system for our product a while back and didn't realize how easy they were to get started. So I put together my learnings into this online course. It's not quite ready but if you sign up and mention HackerNews, I can get you early access. I'm looking to get feedback on the following: (1) materials — is it engaging & did you learn something? (2) UI/UX of the platform — did you have any issues that prevented you from starting or finishing the tutorial? (3)…
2024 · takehomes.com · its alternatives →
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Hey HN, exciting news! Our RAG framework, Cognita (https://github.com/truefoundry/cognita), born from collaborations with diverse enterprises, is now open-source. Currently, it offers seamless integrations with Qdrant and SingleStore. In recent weeks, numerous engineers have explored Cognita, providing invaluable insights and feedback. We deeply appreciate your input and encourage ongoing dialogue (share your thoughts in the comments – let's keep this ‘open source’). While RAG is undoubtedly powerful, the process of building a functional application with it can feel…
2024 · github.com · its alternatives →
- 22Beyond OCR▲12
Fast & Accurate Question-Answering on Complex PDFs
2025 · thirdaiautomation.com · its alternatives →
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Built an automated system to run a deep search of ArXiv and carefully find all the precise papers that exist on a complex topic. It's different from simple RAG because it searches, classifies, and adapts based on relevant papers it uncovers, and then continues until it finds every paper on a topic (trying to mimic the human research process). Benchmarked 10x higher accuracy and total retrieval compared to Google Scholar for a median search (whitepaper on website). Also knows when it is complete, and misses virtually nothing (< 3% or so, once it's converged). Website has a free trial and a…
2024 · app.undermind.ai · its alternatives →
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Ragas is an open-source library for evaluating and testing RAG and other LLM applications. Github: https://docs.ragas.io/en/stable/, docs: https://docs.ragas.io/. Ragas provides you with different sets of metrics and methods like synthetic test data generation to help you evaluate your RAG applications. Ragas started off by scratching our own itch for evaluating our RAG chatbots last year. Problems Ragas can solve - How do you choose the best components for your RAG, such as the retriever, reranker, and LLM? - How do you formulate a test dataset…
2024 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →