Agentset

Agentset is an open-source platform for building AI applications that provide reliable, grounded answers using retrieval-augmented generation (RAG). It is designed to help teams move from prototype to production quickly, without requiring deep expertise in machine learning, LLMOps, or vector databases. By focusing on production-grade RAG workflows, Agentset streamlines the process of connecting large language models to private or domain-specific data sources in a controlled, observable way.

Agentset offers an end-to-end stack for RAG, including data ingestion, chunking, embedding, indexing, retrieval, and response orchestration. It supports integration with common data sources such as documentation, knowledge bases, file stores, and APIs, and provides tools to configure retrieval strategies, prompts, and guardrails. The platform emphasizes reliability through evaluation, monitoring, and experiment tracking, allowing users to compare different RAG configurations, measure answer quality, and reduce hallucinations. As an open-source solution, Agentset can be self-hosted, extended, and integrated into existing infrastructure and CI/CD pipelines.