Progress

Progress Agentic RAG is a managed service that provides a streamlined, fully automated approach to indexing, retrieving, and integrating enterprise data with large language models and AI agents. The core functionality revolves around "agentic retrieval-augmented generation," meaning that instead of manually curating prompts or building complex pipelines, users upload files and documents—such as PDFs, Word files, spreadsheets, or text documents—and the system automatically indexes their content into a searchable vector database. This index is then queried by AI agents or LLMs at inference time to generate contextually accurate answers grounded in the user's own data, eliminating the need for costly fine-tuning or bespoke integrations. The service supports a wide range of use cases, including customer support chatbots that reference product manuals, internal knowledge bases that answer employee questions using company policies, and research assistants that pull relevant sections from hundreds of technical papers. Because indexing is automated and continuous, new documents added to the system become immediately available for retrieval without manual intervention. The platform also provides hooks for AI agents to perform multi-step reasoning: an agent can first search the index, retrieve the top-k relevant passages, then combine them with instructions from a user query to produce a synthesized response, all within a single request cycle. For organizations dealing with high data volumes, Progress Agentic RAG offers scalable ingestion pipelines that handle diverse file formats and metadata extraction. It also includes role-based access control and data residency options, allowing teams to restrict sensitive information from being exposed to unauthorized users. The service is