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Agentset

Open-source RAG platform for production AI chat and search — multimodal ingestion, automatic citations and metadata filtering behind JS and Python SDKs.

freemiumDR 32Free forever: 1,000 pages, 10,000 retrievals per month, community support, no connectors. Pro $49/month: 10,000 pages with $0.01 per additional page, unlimited retrievals, email support, connectors at $100 each, plus Deep Research. Enterprise is custom, adding unlimited pages and retrievals, on-premise or BYOC deployment, SOC 2 / HIPAA / GDPR reports, SSO and dedicated engineering support.View full pricing →

About Agentset

Agentset is an open-source platform for building AI chat and search over your own data without assembling a RAG stack yourself. It covers the whole path — ingestion and chunking across 22-plus file formats, embedding, retrieval, agentic search and answer generation — behind JavaScript and Python SDKs, so a team that needs a reliable answer engine on top of a document corpus can ship one without hiring for retrieval expertise. Three design choices distinguish it from a hand-rolled pipeline. Multimodal handling means images, graphs and tables inside documents are treated as first-class retrievable content rather than being dropped at parse time, which is where most naive pipelines quietly lose half a knowledge base. Citations are automatic, so every answer carries inspectable sources — the single most effective mitigation for hallucinated answers in a customer-facing deployment. And metadata filtering lets a query be scoped to a subset of the corpus, which is what makes per-tenant or per-permission answering possible. The project publishes benchmark positions on MultiHopQA and FinanceBench and provides customisable preview links so non-technical stakeholders can test a deployment and leave feedback without an account. Supported inputs include PDF, DOCX, XLSX, PPTX, HTML, CSV, Markdown, email formats and common image types.

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Key Features

End-to-end RAG: ingestion, chunking, retrieval, agentic search
Multimodal — images, graphs and tables retrieved like text
Automatic citations on every answer for source inspection
Metadata filtering to scope answers to a data subset
22+ file formats with JavaScript and Python SDKs
Shareable preview links for external feedback

Tags

ragopen-sourcesearchsdkdeveloper-tools
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