Agentset

What it does

Open-source RAG infrastructure that survives production workloads. Upload documents, query via API, get answers with sources. Hybrid search, multimodal, complex reasoning - all included. Model-agnostic. Used by 1,500+ teams in medical AI, legal tech, enterprise search.

The open-source platform to build AI apps that deliver reliable answers. Production-grade RAG in minutes, no expertise needed.

Agentset helps developers build AI apps that deliver reliable answers. No RAG expertise needed. Get superb accuracy on your data before any customizations. Industry setting benchmarks for MultiHopQA ¹ and FinanceBench ² . Agentset natively works with images, graphs, and tables just like text. Answer questions from every part of your knowledge base. Agentset automatically cites the sources of your answers, allowing your users to inspect it. Agentset supports metadata filtering, allowing you to base answers on a subset of the data. Agentset allows you to capture external feedback quickly using a customizable chat interface. JavaScript and Python SDKs to upload your data with 22+ file formats…from agentset.ai

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  AgentSea2025 · agentsea.com · ▲439

  Today we’re excited to introduce AgentSea, a private AI chat built for sensitive work. When you use closed-source AI models, your data can: – be stored – pulled into training pipelines – shared with third parties That might be fine if you’re making memes or drafting LinkedIn posts. But it becomes a serious risk when you’re pasting contracts, health info, financial data, or business secrets. That’s why we built AgentSea. In Secure Mode, all chats run on open-source models or models hosted on our own servers. Your data never leaves, is never used for training, and is never leaked. Agentsea…

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  aoyo.ai2024 · ▲126

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  Query MemoryMar 2026 · querymemory.com · ▲100

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  Agentset – Open-source RAG with vector DB, embeddings, and API built-in2025 · github.com · ▲6

  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.…

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  Pastors.ai2023 · pastors.ai · ▲107

  I made a chatbot-based search engine that does agentic RAG using the Youtube channels, websites, and google reviews of all churches in Boulder, CO I tried a couple different approaches to this, but the one I'm currently liking is a MapReduce approach that takes a query, does some pre-filtering, and maps it to the individual vector databases of all the churches. Then the Reduce step synthesizes the individual church results to return the response to a user For example, if you ask it "LQBTQ-friendly church" it will loop through asking all the individual churches the question "Are you…

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