Alternatives
Products that do what Agentset – Open-source RAG with vector DB, embeddings, and API built-in does
Hi HN, We built one of the largest RAG set-ups that exist toady with Usul.ai (6B tokens). We started by using langchain and llamaindex, they were able to get us to a prototype in a couple of days, but took 3 months of taking pieces apart and optimizing them to make it perform well at such large scale. We put all of these learning into an MIT licensed open-source project — Agentset. Our goal to let people get production quality RAG w/o having to understand or optimize the underlying pieces. It supports 22 file formats, agentic search, deep research, citations, and a UI out of the box.…
- 1
- 2TA
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
- 3JA
Hello HN, I don't post on here much, but wanted to get some eyes on a new project I'm just launching. I think we definitely need one more AI code agent.. I'm a long-term C++ dev, and over 30+ years I've created some successful audio dev tools (JUCE, the Tracktion DAW, the Cmajor DSP language). All of these came from me getting annoyed with something I had to use, and deciding to have a go at my own take on whatever it was. So Juggler is my attempt at an AI code agent, after spending too many hours loving what the models could do, but hating the CLI experience, and having some opinions of…
Jul 2026 · github.com
- 4
- 5HW
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
- 6
- 7
- 8
13,000+ MCP servers, skills & plugins for AI coding agents
Jul 2026 · codexmarketplaces.com
- 9AI
Hi HN, we’re Sai and Aayush, and we’re building Hypercubic (https://www.hypercubic.ai/), bringing AI tools to the mainframe and COBOL world. (We did a Launch HN last year: https://news.ycombinator.com/item?id=45877517.) Today we’re launching Hopper, an agentic development environment for mainframes. You can download it here: https://www.hypercubic.ai/hopper, and you can also request access and immediately get a mainframe user account to play with. There's also a video runthrough at https://www.youtube.com/watch?v=q81L5DcfBvE.…
May 2026 · hypercubic.ai
- 10
- 11OS
Hey HN! We’ve published a series of open-source notebooks showcasing Advanced RAG and Agentic architectures, and we’re excited to share our latest compilation of Agentic RAG techniques! These Colab-ready notebooks are designed to be plug-and-play, making it easy to integrate them into your projects. We're actively expanding the repository and would love your input to shape its future. What Advanced RAG technique should we add next? Drop your ideas in the comments or open an issue on GitHub!
2025 · github.com
- 12AA
We’ve published a set of open-source reference implementations on how to build production-grade Agentic AI applications on AWS. What’s in the repo: • Agentic RAG, memory, and planning workflows with LangGraph & CrewAI • Strands-based flows with observability using OTEL & Arize • Evaluation with LLM-as-judge and cost/performance regressions • Built with Bedrock, S3, Step Functions, and more GitHub: https://github.com/aws-samples/sample-agentic-frameworks-on-... Would love your thoughts — feedback, issues, and stars welcome!
2025 · github.com
- 13
Smarter RAG with Agentic Retrieval & Context-Aware MCP
Sep 2025
- 14AC
I'm Anand, co-founder and CTO of Altimate AI. My co-founder Pradnesh and I are open-sourcing Altimate Code. AMA. Why we built this: Pradnesh and I have been building tooling for data engineers for three years: dbt Power User and Datamates vscode extensions with combined 750k+ installs, running against real Fortune 500 data estates. The pattern we kept seeing: general-purpose agents can write SQL, but they have no model of what the SQL does. No lineage. No schema context. No understanding of what's in a dbt manifest. That's not a prompt problem; it's a missing tool layer problem. The numbers…
Mar 2026 · github.com
- 15
- 16PR
Hi HN, While building RAG agents, I noticed a lot of token budget was wasted on formatting overhead (HTML tags, JSON structure, whitespace). Existing solutions felt too heavy (often requiring torch/transformers), so I wrote this lightweight, zero-dependency library to solve it. It includes strategies for context packing, PII redaction, and tool output compression. Benchmarks show it can save ~15% of tokens with negligible latency overhead (<0.5ms). Happy to answer any questions!
Dec 2025 · github.com
- 17AE
Hi all, Sharing a repo I was working on for a while. It’s open-source and includes many different strategies for RAG (currently 17), including tutorials, and visualizations. This is great learning and reference material. Open issues, suggest more strategies, and use as needed. Enjoy!
2024 · github.com
- 18WB
Hi HN, Our research team just released the best performing and most efficient reranker out there, and it's available now as an open weight model on HuggingFace. Reranker v2 was designed specifically for agentic RAG, supports instruction following (our v1 was the first to introduce this), and is multilingual. Along with this, we're also open source our eval set, which allows you to reproduce our benchmark results. By releasing these datasets, we are also advancing instruction-following reranking evaluation, where high-quality benchmarks are currently limited. Please give it a try and let us…
2025 · huggingface.co
- 19
Enterprise RAG, autonomous agents & production AI books.
Jul 2026 · useagenticx.com
- 20IB
Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
Oct 2025 · github.com
- 21AF
Mar 2026 · agentmeet.net
- 22SW
Hey HN, We’re Basia, Fokke, and Geno from Liquidmetal AI, and we built something we wish we had a long time ago: SmartBuckets. We’ve spent a lot of time building RAG and AI systems, and honestly, the infrastructure side has always been a pain. Every project turned into a mess of vector databases, graph databases, and endless custom pipelines before you could even get to the AI part. SmartBuckets is our take on fixing that. It works like an object store, but under the hood it handles the messy stuff — vector search, graph relationships, metadata indexing — the kind of infrastructure you'd…
2025
- 23HO
gm gm, We’re excited to show our project, Hive Network, a new frontier for decentralized AI agents that operate both on-chain and off-chain. Our mission is to make AI more powerful and transparent, and we’re inviting you to join us in this revolution. What is Hive Network AI? -- Hive Network AI is a platform where developers can create, deploy, and manage AI agents that function autonomously across blockchain and traditional networks. Our system addresses significant issues in the AI space, such as the lack of transparency, difficulty in monetizing models, and insufficient research funding.…
2024 · hivenetwork.ai
- 24PA
We're excited to release PaperQA2, an open source RAG library specialized to work with the scientific literature. We've seen some really compelling results with it (https://paper.wikicrow.ai), like superhuman performance at question answering and summarization when compared with expert scientists. PaperQA2 is a major overhaul of our prior PaperQA system, it includes automatically obtained rich metadata for each paper, a CLI to work with local papers directly, a local full-text search engine for keywords searches over PDF files, a state-of-the-art algorithm for LLM-based re-ranking…
2024 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →