Graphwise builds a semantic layer that transforms fragmented enterprise data into governed knowledge graphs for AI applications. The stack spans Java, Rust, C++, and Go with GraphDB at its core, complemented by Kafka, Snowflake, and Databricks for data pipelines — a pattern indicating deep investment in both real-time graph operations and batch analytics integration. Active hiring across engineering, marketing, and support at mid-to-senior levels suggests scaling beyond early adoption into production deployment and customer success phases.
Graphwise helps enterprises connect data silos and ground search, analytics, and AI applications in reliable, governed context. The company was formed through a merger combining decades of knowledge-graph and semantic-technology expertise. The product architecture centers on transforming unstructured and structured data into a knowledge graph that acts as a single source of truth, reducing AI hallucination risk and enabling measurable ROI at scale. The platform targets organizations where data precision and governance are mission-critical, with a global team spanning North America, Europe, and APAC.
Core languages: Java, Rust, C++, Go. Database: GraphDB. Cloud: AWS, Azure. Data pipelines: Kafka, Snowflake, Databricks, Apache Airflow, Talend. Orchestration: Kubernetes, Terraform. Documentation: Arc42.
New York, NY. The company has a global team of over 200 employees across North America, Europe, and APAC, with current hiring activity in Austria.
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.