Production-oriented RAG
Agentset is built for production RAG, with a focus on reliable answers, citations, and retrieval quality rather than demo-only workflows.
Agentset
Agentset is an open-source platform for building AI chat and search on private or internal knowledge bases, with citations, multimodal documents, and free, Pro, and enterprise plans.
Overview
Agentset is an open-source platform for building AI chat and search experiences on top of private or internal knowledge bases. It is positioned for developers who want production-ready RAG without building and maintaining the entire retrieval pipeline themselves.
The product emphasizes reliable answers, citations, and support for real-world documents. Its home page highlights multimodal retrieval across text, images, graphs, and tables, while the pricing page shows tiers for free use, production applications, and enterprise deployments.
Features
Multimodal document support
The platform supports images, graphs, and tables alongside text so users can ask questions across richer document sets.
Citations and sources
Answers can include source citations, which lets users inspect where a response came from and review supporting material.
Metadata filtering
Metadata filters let teams narrow retrieval to a subset of content when they need scoped answers.
Developer tooling
Developers can ingest content through JavaScript and Python SDKs, with support for 22+ file formats and an MCP server for external applications.
Model-agnostic integration
Agentset can work with an AI SDK integration and lets teams choose their own vector database, embedding model, and LLM.
Use Cases
Product search and Q&A
Build a chat or search layer over internal documents and knowledge bases where answers need citations and controlled retrieval instead of generic chatbot responses.
Document knowledge bases
Index document libraries that include PDFs, HTML pages, office files, and other supported formats, then let users search across them with filtering and source tracing.
Synced team content
Connect external sources such as Google Drive, SharePoint, or Notion so content stays synchronized with the knowledge base as those systems change.
Embedded application workflows
Expose the same knowledge base to other applications through the MCP server or AI SDK integration when you need the retrieval layer inside a larger product.
Scaled production deployments
Use the platform for teams that need production deployment options, custom workflows, or enterprise support rather than a single-purpose prototype.
Pros and Cons
Pros
- Supports citations, hybrid search, reranking, and metadata filters for more controlled retrieval.
- Handles multiple file types and multimodal content, including images, graphs, and tables.
- Offers JavaScript and Python SDKs plus an MCP server for developer integration.
- Provides a clear pricing path from free use to production and enterprise deployments.
- Lets teams choose their own vector database, embedding model, and LLM.
Cons
- The source does not spell out a step-by-step setup flow or onboarding process.
- Free and Pro plans do not include custom integrations, which are reserved for Enterprise according to the pricing page.
- Some enterprise capabilities, such as on-premise or BYOC deployment and compliance reports, are only listed on the Enterprise plan.
FAQ
What is Agentset for?
Agentset is an infrastructure product for developers building production-ready RAG applications. The home page describes it as a platform for search and Q&A inside products, and the pricing page shows plans for personal use, production applications, and enterprise workflows.
How do teams integrate Agentset into an existing stack?
The source does not present a detailed setup flow, but it does show JavaScript and Python SDKs, an MCP server, and an AI SDK integration, which suggests it is intended to plug into existing development stacks.
What kinds of content can Agentset process?
Agentset supports file-based ingestion for many common formats, including text, HTML, PDF, and office-style documents, and it also supports external data connectors for services such as Google Drive, SharePoint, and Notion.
Does Agentset have plans for different team sizes?
Yes. The pricing page includes a Free plan, a Pro plan for production applications, and an Enterprise plan with custom workflows and deployment options. The site also says plans can be upgraded or downgraded.
What output or retrieval features does Agentset provide?
The source shows that Agentset can return citations and source references with answers, and it supports metadata filtering, hybrid search, reranking, and multimodal content such as images, graphs, and tables.
Quick Facts
- Category
- Developer Tool / AI Search
- Platform
- Open-source web platform
- Primary users
- Developers building RAG, chat, and search apps
- Pricing
- Free plan, Pro plan, and custom Enterprise pricing
- Integrations
- JavaScript SDK, Python SDK, AI SDK, MCP server, and external data connectors
- Source domain
- agentset.ai
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