SupportAI Overview

SupportAI is the second component of TigerGraph CoPilot.

It is designed to ingest a set of documents, extract a knowledge graph from the information, and enable hybrid search of the documents and graph data through natural language queries. This functionality will enrich RAG (Retrieval-Augmented Generation) pipelines with graph data, enabling more accurate and informative responses to user queries.

Support AI Architecture

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With SupportAI, CoPilot creates chatbots with graph-augmented AI on a user’s own documents or text data.

It builds a knowledge graph from source material and applies its unique variant of graphRAG (graph-based Retrieval Augmented Generation) to improve the contextual relevance and accuracy of answers to natural-language questions.

CoPilot will also identify concepts and build an ontology, to add semantics and reasoning to the knowledge graph, or users can provide their own concept ontology.

Then, with this comprehensive knowledge graph, CoPilot performs hybrid retrievals, combining traditional vector search and graph traversals, to collect more relevant information and richer context to answer users’ knowledge questions.

Organizing the data as a knowledge graph allows a chatbot to access accurate, fact-based information quickly and efficiently, thereby reducing the reliance on generating responses from patterns learned during training, which can sometimes be incorrect or out of date.

Next Steps

Next, go to Contribute see how you can contribute to TigerGraph CoPilot.

Return to TigerGraph CoPliot for a different topic.