Verbis Graph Engine – GraphRAG Knowledge Retrieval

Verbis Graph Engine is a container-based GraphRAG (graph-enhanced retrieval augmented generation) knowledge retrieval engine designed for developers and enterprises working with complex document-based AI workflows.

Unlike traditional vector-only RAG solutions, Verbis Graph Engine combines semantic vector embeddings with structured knowledge graph traversal. This hybrid approach enables multi‑document reasoning, entity‑aware retrieval, and more accurate responses for complex queries that span multiple sources.

A free demo container is available to support functional testing and technical evaluation. The demo is delivered as a standard container image compatible with Microsoft Azure container services and provides a fully functional evaluation environment.

Professional and enterprise editions are available for teams requiring expanded capacity and production deployments.

Key capabilities include:

• GraphRAG-based retrieval combining vector similarity and knowledge graph relationships
• Multi-document reasoning across uploaded content
• Integrated FastAPI backend with OpenAPI (Swagger) documentation available at /docs
• Web‑based Streamlit interface for document management and chat‑based querying
• Health endpoint for orchestration and monitoring at /_stcore/health

Deployment and usage notes:

• Runs as a single‑container instance
• Data is retained only for the lifetime of the container and user account
• Persistence across container redeployment is not guaranteed
• No license keys, subscriptions, or in‑app purchases are required for the free demo
• Azure infrastructure costs apply based on the selected deployment configuration

This solution is intended for data scientists, developers, solution architects, and AI teams building and operating graph‑based knowledge retrieval systems on their own documents across evaluation, pilot, and production environments.