RustyRAG
The Fastest RAG API
RustyRAG launched on March 28, 2026 with 3 votes, #3,303 of 23,380 launches that month and more than 50% of that year's launches.
What it does
Open-source RAG API written in Rust. Sub-200ms time to first token, 94.5% accuracy on 3,000+ questions. Hybrid search with reranking, streaming answers. Upload PDFs, ask questions, get answers fast. Self-host the whole thing in minutes. Connect knowledge to your Voice AI, AI Agents and any product where retrieval speed is the bottleneck.
Production-grade RAG API built in Rust. Hybrid search with HNSW dense vectors and BM25 sparse matching, cross-encoder reranking, layout-aware document extraction via Docling, and 94.5% accuracy on Open RAG Bench. Powered by Cerebras, Groq, Milvus, and Jina AI. - RustyRAG/RustyRAG
Does a similar job
all alternatives →
FastGraphRAG – Better RAG using good old PageRank2024 · github.com · ▲457Hey 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…
IgnitionRAGApr 2026 · ignitionrag.com · ▲83Multimodal RAG platform, from POC to production in minutes
SeekStorm – open-source sub-millisecond search in Rust2024 · github.com · ▲245SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust. - SeekStorm/SeekStorm
SpRAG – Open-source RAG implementation for challenging real-world tasks2024 · github.com · ▲69Hey HN, I’m Zach from Superpowered AI (YC S22). We’ve been working in the RAG space for a little over a year now, and we’ve recently decided to open-source all of our core retrieval tech. spRAG is a retrieval system that’s designed to handle complex real-world queries over dense text, like legal documents and financial reports. As far as we know, it produces the most accurate and reliable results of any RAG system for these kinds of tasks. For example, on FinanceBench, which is an especially challenging open-book financial question answering benchmark, spRAG gets 83% of questions correct,…
More ai this month
the category →
Paintings by AI models: programs run through a simulation of oil paint.
AI · 22d ago · stillwet.art
FastRouter.ai▲364Route requests to the right LLM for cost, latency & quality
AI · 23d ago · fastrouter.ai
Source: Product Hunt launch ↗
Launched alongside, March 2026
the whole month →
Switch from ChatGPT to Claude with import memory feature
AI · Mar 2026 · claude.com
Littlebird▲709Littlebird remembers everything across your meetings, messages, docs, and apps, then takes action so you can recall any detail and never lose context.
AI · Mar 2026 · littlebird.ai
