Byne

Progress Agentic RAG is a SaaS Retrieval-Augmented Generation platform that automatically indexes, searches, and generates AI-powered insights from structured and unstructured business data, including documents, emails, video, slides, and more, by combining RAG with agentic workflows that reason, classify, summarize, and answer queries with traceable, verifiable results without requiring users to build and manage their own RAG infrastructure. Designed as a modular no-code RAG-as-a-Service solution, it accelerates AI readiness by letting organizations extract contextual intelligence and business knowledge using natural language queries and quality-driven output metrics while integrating with any leading Large Language Model (LLM) and supporting multilingual, multimodal content indexing and retrieval. Features include AI summarization and classification, generated Q&A from enterprise data, a Prompt Lab for validating LLM behavior with custom prompts.

Vectorize is a platform designed to transform unstructured data into optimized vector search indexes, facilitating retrieval-augmented generation pipelines. It enables users to import documents or connect to external knowledge management systems, allowing Vectorize to extract natural language suitable for LLMs. The platform evaluates multiple chunking and embedding strategies in parallel, providing recommendations or allowing users to choose their preferred methods. Once a vector configuration is selected, Vectorize deploys it into a real-time vector pipeline that automatically updates with any data changes, ensuring accurate search results. The platform offers connectors to various knowledge repositories, collaboration platforms, and CRMs, enabling seamless integration of data into generative AI applications. Additionally, Vectorize supports the creation and updating of vector indexes in preferred vector databases.