Retrivora AI

Retrivora provides a plug-and-play Retrieval Augmented Generation (RAG) engine designed for rapid deployment. Key features include: * Universal document ingestion (PDF, DOCX, CSV, JSON, MD) * Seamless integration with leading vector databases (Pinecone, pgvector, MongoDB, Milvus, Qdrant) * Support for multiple large language models (OpenAI, Anthropic, Google, Meta, Mistral) * Real-time RAG pipeline monitoring and observability * Developer-friendly SDK (TypeScript, Python, REST APIs) with sub-5 minute deployment This platform streamlines the process of connecting proprietary data to generative models, enabling developers to build grounded and reliable applications without complex infrastructure setup. It handles data parsing, chunking, metadata enrichment, semantic search, reranking, and context assembly, ensuring accurate and relevant responses with cited sources. Retrivora is ideal for engineering teams and developers looking to quickly deploy enterprise-grade RAG pipelines. It offers robust security, scalability, and compliance, making it suitable for critical applications requiring reliable data retrieval and contextual response generation across various industries.