Agentset.ai

New4.5

Agentset.ai is an open-source, local-first semantic search and Retrieval-Augmented Generation (RAG) platform built for teams that want full control over their data. Instead of sending documents to third-party cloud services, you can index, search, and query your own text collections entirely on your own infrastructure. Agentset.ai turns scattered files, notes, and knowledge bases into a searchable, conversational knowledge layer that your applications and agents can use in real time. With Agentset.ai, you can plug modern embedding models into a fast local index, then use RAG to provide your LLMs with precise, document-grounded context. This dramatically improves answer accuracy, traceability, and compliance, while reducing hallucinations. The system is designed to be developer-friendly, with clear APIs, simple configuration, and flexible integration into existing backend services, chatbots, or internal tools. Because it is open source, Agentset.ai can be customized to your security, performance, and workflow requirements. You decide how data is stored, how models are deployed, and what retrieval strategies to use. Whether you are building internal knowledge assistants, developer copilots, or customer support tools, Agentset.ai gives you a robust semantic search and RAG backbone that stays close to your data and scales with your use cases.