Graph database and GraphRAG platform grounding enterprise LLMs in facts
Graphwise sells semantic infrastructure built on its GraphDB engine and GraphRAG tooling, aimed at anchoring enterprise LLMs to verifiable knowledge graphs. The stack pairs systems languages (Rust, C++, Go, Java) with gRPC and Kubernetes across AWS, Azure and GCP, which points to a multi-cloud database product rather than a services shop. Hiring is steady and senior-weighted, with engineering focused on GraphRAG architecture and automated graph construction.
Graphwise builds an enterprise platform that combines graph databases, AI-assisted data modeling, automated pipelines and GraphRAG for production AI use cases. The company formed through the merger of Ontotext and Semantic Web Company and is headquartered in New York, NY. It has a 51–200 employee range on LinkedIn and runs offices across North America, Europe and APAC. Its focus areas include semantic layers, knowledge management, text analysis and semantic annotation. Go-to-market runs on Salesforce, HubSpot and ZoomInfo.
Graphwise uses Java, Rust, C++, Go, Scala and Python with gRPC, its own GraphDB and GraphRAG, Kubernetes and Terraform on AWS, Azure and GCP, plus Salesforce and HubSpot for sales.
Job posts point to GraphRAG and graph automation architecture, scalable data ingestion and enrichment pipelines, automated graph construction, and finance process automation including centralized cash collection.
Graphwise is headquartered in New York, NY, with offices across North America, Europe and APAC following the merger of Ontotext and Semantic Web Company.
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Graphwise's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.