Indexed Knowledge, On Demand
A production-grade RAG platform that turns your documents into an intelligent knowledge base. Upload files, ask questions, and get accurate answers grounded in your data — with knowledge graphs, hybrid search, and self-correcting retrieval.
Kova combines dense vector search with BM25 keyword search using Reciprocal Rank Fusion, then reranks results with a cross-encoder for 33-40% better accuracy. LightRAG-powered knowledge graphs extract entities and relationships, enabling multi-hop reasoning across your entire document library.
Unlike basic RAG systems, Kova evaluates retrieval quality in real-time. If results are insufficient, it rewrites queries and retries — falling back to graph search when needed. Four quality tiers let you trade speed for thoroughness depending on the question.
Multi-tenant architecture with org, tenant, and user-level access scoping. API key management for third-party integrations. Supports PDF, DOCX, PPTX, Markdown, CSV, HTML, and images with intelligent document parsing and contextual enrichment before embedding.
Kova is a cutting-edge Retrieval-Augmented Generation platform built for teams that need accurate, grounded answers from their own documents. It combines hybrid search (dense + sparse), cross-encoder reranking, knowledge graph extraction, and a self-correcting retrieval loop (CRAG) to deliver answers that are actually trustworthy. Multi-tenant by design, Kova supports PDF, DOCX, PPTX, Markdown, CSV, images, and more — with a 4-tier quality ladder from fast single-call responses to thorough multi-step reasoning.
