AI · alternatives · 2026
24 alternatives to R2R V2 – A open source RAG engine with prod features
Hi HN! We're building R2R [https://github.com/SciPhi-AI/R2R], an open source RAG answer engine that is built on top of Postgres+Neo4j. The best way to get started is with the docs - https://r2r-docs.sciphi.ai/introduction. This is a major update from our V1 which we have spent the last 3 months intensely building after getting a ton of great feedback from our first Show HN (https://news.ycombinator.com/item?id=39510874). We changed our focus to building a RAG engine instead of a framework, because this is what developers asked for the most.…
R2R V2 is an open source retrieval-augmented generation (RAG) engine built on Postgres and Neo4j. It is designed for developers building question-answering systems. The engine includes multimodal data ingestion, hybrid… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. R2R V2 – A open source RAG engine with prod features launched in 2024; newer entries below may have overtaken it.
- 1
Hello HN, I'm Owen from SciPhi (https://www.sciphi.ai/), a startup working on simplifying˛Retrieval-Augmented Generation (RAG). Today we’re excited to share R2R (https://github.com/SciPhi-AI/R2R), an open-source framework that makes it simpler to develop and deploy production-grade RAG systems. Just a quick reminder: RAG helps Large Language Models (LLMs) use current information and specific knowledge. For example, it allows a programming assistant to use your latest documents to answer questions. The idea is to gather all the relevant information…
2024 · github.com · its alternatives →
- 2
- 3
- 4
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 →
- 5
Reor is an open-source AI note-taking app that runs models locally. The four main things to know are: 1. Notes are connected automatically with vector search. You can do semantic search + related notes are automatically connected. 2. You can do RAG Q&A on your notes using the local LLM of your choice. 3. Embedding model, LLM, vector db and files are all run or stored locally. 4. Point it to a directory of markdown files (like an Obsidian vault) and it works seamlessly alongside Obsidian. Under the hood, Reor uses Llama.cpp (node-llama-cpp integration), Transformers.js and Lancedb to power…
2024 · github.com · its alternatives →
- 6
- 7
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 →
- 8
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 →
- 9
Hi HN, I am Jiayuan, and I'm here to introduce a tool we've been building over the past few months: Devv (https://devv.ai). In simple terms, it is an AI-powered search engine specifically designed for developers. Now, you might ask, with so many AI search engines already available—Perplexity, You.com, Phind, and several open-source projects—why do we need another one? We all know that Generative Search Engines are built on RAG (Retrieval-Augmented Generation)[1] combined with Large Language Models (LLMs). Most of the products mentioned above use indexes from general search engines…
2024 · devv.ai · its alternatives →
- 10
Vectorize 2.0▲335Complete RAG agents (chatbot, MCP) with little or no code
2025 · platform.vectorize.io · its alternatives →
- 11
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 →
- 12
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 →
- 13
Hey HN! We’re Jorge and Will from Lotas (https://www.lotas.ai/), and we’ve built Erdos, a secure AI-powered data science IDE that’s fully open source (https://www.lotas.ai/erdos). A few months ago, we shared Rao, an AI coding assistant for RStudio (https://news.ycombinator.com/item?id=44638510). We built Rao to bring the Cursor-like experience to RStudio users. Now we want to take the next step and deliver a tool for the entire data science community that handles Python, R, SQL, and Julia workflows. Erdos is a fork of VS Code designed for data…
Oct 2025 · lotas.ai · its alternatives →
- 14
Hey HN! We're Phil and Ming, co-founders of Retake (https://github.com/getretake/retake). Retake is an open source tool that adds keyword and semantic (i.e hybrid) search to databases. We’ve started by extending the capabilities of Postgres with an SDK for lightning-fast queries. We built Retake to fix two issues: keeping vectors in sync with Postgres in real time is difficult, and most vector databases aren’t built for hybrid search. A quick refresher: “keyword search” refers to a technique where results are scored based on the appearance of exact words or terms.…
2023 · github.com · its alternatives →
- 15SA
Hi HN, I’m Tullie, founder of Shaped. Previously, I was a researcher at Meta AI, worked on ranking for Instagram Reels, and was a contributor to PyTorch Lightning. We built ShapedQL because we noticed that while retrieval (finding 1,000 items) has been commoditized by vector DBs, ranking (finding the best 10 items) is still an infrastructure problem. To build a decent for you feed or a RAG system with long-term memory, you usually have to put together a vector DB (Pinecone/Milvus), a feature store (Redis), an inference service, and thousands of lines of Python to handle business logic…
Jan 2026 · playground.shaped.ai · its alternatives →
- 16
Papr▲113Predictive memory and context intelligence API for AI Agents
Dec 2025 · papr.ai · its alternatives →
- 17
TL;DR: Vector-based RAG performs poorly for many real-world applications like codebase chats, and you should consider 'language maps'. Part of our mission at Mutable.ai is to make it much easier for developers to build and understand software. One of the natural ways to do this is to create a codebase chat, that answer questions about your repo and help you build features. It might seem simple to plug in your codebase into a state-of-the-art LLM, but LLMs have two limitations that make human-level assistance with code difficult: 1. They currently have context windows that are too small to…
2024 · twitter.com · its alternatives →
- 18IB
We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of…
2025 · blog.kuzudb.com · its alternatives →
- 19
Korvus▲122Search SDK to unify RAG pipeline in a single database query
2024 · github.com · its alternatives →
- 20
Polygres▲58Polygres turns the Postgres you already run into internal search for AI agents. Rows, relationships, and embeddings: one hybrid query, one ranked answer.
Jul 2026 · polygres.com · its alternatives →
- 21
- 22
Hey HN, Joe and Ethan from Tonic.ai here. We just released a new open-source python package for evaluating the performance of Retrieval Augmented Generation (RAG) systems. Earlier this year, we started developing a RAG-powered app to enable companies to talk to their free-text data safely. During our experimentation, however, we realized that using such a new method meant that there weren’t industry-standards for evaluation metrics to measure the accuracy of RAG performance. We built Tonic Validate Metrics (tvalmetrics, for short) to easily calculate the benchmarks we needed to meet in…
2023 · github.com · its alternatives →
- 23
We’ve recently open-sourced Model2vec, a method to distill sentence transformers into static embeddings that outperform all previous approaches by a large margin on MTEB. Our new models set a new state-of-the-art for static embeddings. Main features: - Our best model (potion-base-8M) has only 8M parameters, which is ~30mb on disk - Inference is ~500x faster than the distilled base model (bge-base), on a CPU - New models can be distilled in 30 seconds on a CPU without requiring a dataset - just a vocabulary - Numpy-only inference: The packaged can be install the package with minimal…
2024 · github.com · its alternatives →
- 24
Ragas is an open-source library designed for evaluating and testing RAG (Retrieval-Augmented Generation) and other LLM applications. It offers a diverse set of metrics and methods, including synthetic test data generation, to help you assess your RAG applications. Ragas was initially developed to address our own needs for evaluating RAG chatbots last year. ### Problems Ragas Can Solve: - How can you select the best components for your RAG, such as the retriever, reranker, and LLM? - How can you create a test dataset without incurring significant expenses and time? We believe there's a need…
2024 · github.com · its alternatives →
Also compare
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 →