Graphwise, a top provider in the Graph AI space, has announced the immediate availability of GraphRAG, a low-code AI workflow engine built to help enterprises move beyond experimental AI projects. With this launch, the company aims to transform simple “Python prototypes” into fully operational, production-grade AI systems without the long development cycles that often slow down innovation.
To begin with, GraphRAG introduces a trusted semantic layer that significantly reduces AI hallucinations while delivering more precise and verifiable responses. Unlike traditional Retrieval-Augmented Generation (RAG) systems, which often break information into disconnected chunks, GraphRAG keeps enterprise knowledge intact by treating the knowledge graph as a reliable semantic backbone. As a result, AI outputs remain grounded in factual business data and complex relationships that matter most in real-world decision-making.
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Moreover, Graphwise highlighted the performance impact of combining GraphRAG with ontology-based knowledge graphs. The company demonstrated that enhancing HippoRAG widely considered one of the strongest GraphRAG systems with ontology support cuts inaccurate answers by more than twice on the highly respected MuSiQue benchmark.
MuSiQue, short for Multihop Questions via Single-hop Question Composition, is designed to evaluate advanced RAG systems on difficult reasoning tasks rather than basic fact lookup. This makes it one of the most challenging benchmarks available.
“The MuSiQue dataset is a clear step forward toward better GraphRAG benchmarking,” said Alan Morrison, Independent Graph Technology Analyst and author of The GraphRAG Curator. “The test proved that Graphwise’s approach for semantic GraphRAG consistently outperforms one of the best GraphRAG systems, which uses a schemaless associative graph. While most of the GraphRAG offerings on the market today use the same schemaless approach, customers should be demanding the level of accuracy that comes with ontologies and fully-fledged use of graph databases.”
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In addition, Graphwise positions GraphRAG as a bridge between complex enterprise data and functional AI agents. Many organizations struggle to push AI prototypes into real deployment, but GraphRAG provides a low-code, production-ready foundation that anchors AI agents in enterprise truth.
Key capabilities include a low-code visual engine, pre-built templates for faster deployment, and a semantic metadata control plane that boosts accuracy from 60% to over 90%. The platform also delivers explainability panels, visual debugging tools, and concept enrichment so AI can understand company-specific language and terminology.
“Enterprises are increasingly tired of brittle RAG pipelines that result in shallow retrieval, answer drift, disappearing business logic, and knowledge trapped in silos,” said Andreas Blumauer, SVP Growth at Graphwise. “Because GraphRAG is based on a solid knowledge graph foundation, it removes traditional obstacles by transforming data into a trusted semantic backbone. New no-code capabilities make it easy to deploy intelligent agent-based systems and powerful AI applications to automate knowledge quickly and easily so organizations can make generative AI reliable and scalable for businesses.”
With GraphRAG, Graphwise is pushing enterprise AI toward a future that is more accurate, transparent, and ready for scale.
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