Overview
Agentset: Multimodal RAG engine
Agentset provides a production-ready retrieval-augmented generation engine engineered to help developers build high-accuracy AI search and chat interfaces. Supporting over twenty document and graphic formats, including spreadsheet files, images, and text documents, the system processes multi-modal inputs through dedicated Python and JavaScript software development kits. The architecture analyzes structured tables, dynamic graphs, and visual components directly, ensuring complex knowledge repositories remain fully queryable without lost context. Every answer generated by the platform includes automated source citations and supports custom metadata filtering, allowing precise response scoping across defined enterprise datasets. Development teams benefit from pre-built UI components and customizable chat modules that simplify end-user feedback collection and deployment. Although real-time data streaming features are currently restricted, the platform achieves high performance on retrieval benchmarks like FinanceBench and MultiHopQA. Ultimately, Agentset empowers software engineers to deploy trustworthy knowledge retrieval applications rapidly while maintaining full transparency over data provenance and source material accuracy.