Agentset: Build AI Chat and Search

# Agentset Agentset is an open-source platform designed for building production-ready Retrieval-Augmented Generation (RAG) applications. It enables developers and enterprises to integrate large language models (LLMs) with their own data sources to produce more accurate, context-aware, and verifiable AI responses. By combining hybrid search, deep research, and automated citation tracking, Agentset empowers users to minimize hallucinations and improve reliability across AI-powered workflows. Built by developers for developers, Agentset provides SDKs, APIs, and flexible deployment options to accelerate RAG adoption. Its platform is compatible with major AI providers, vector databases, and cloud infrastructures, offering both managed and self-hosted environments. As a fully open-source solution, Agentset distinguishes itself by offering transparency, customization freedom, and cost efficiency for organizations seeking to move beyond proprietary RAG systems. Agentsets focus on document-centric retrieval, agentic reasoning, and security-first architecture positions it as a leading choice for teams building next-generation intelligent assistants, document retrieval systems, and enterprise knowledge tools. --- ## Core Products & Services ### Agentset RAG Platform - **What it does:** Provides end-to-end infrastructure for retrieval-augmented generation, enabling developers to connect large language models to organization-specific data. Agentset handles document processing, embedding, vector storage, and hybrid search to deliver grounded AI responses with full source attribution. - **Who uses it:** Developers, data teams, and enterprises building intelligent document-based applications and assistants. - **Key features:** - Hybrid search and reranking for high-precision retrieval - Deep research mode for in-depth contextual understanding - Automatic source citations for transparency - Metadata filtering for refined results - Seamless ingestion of over 22 docume