Real-time machine learning platform for fraud and AML detection
DataVisor, a Mountain View company founded in 2013, builds real-time fraud and anti-money-laundering detection for financial institutions, payment providers and digital businesses. Its stack pairs streaming infrastructure (Kafka, Flink, Spark, Cassandra, HBase) with GPU-backed ML tooling (CUDA, PyTorch, TensorFlow) plus Bedrock and MCP, pointing toward agentic AI work. Senior-weighted hiring spans engineering and customer support, alongside work to tighten Salesforce-to-finance data flows.
DataVisor provides an AI-based decisioning platform that detects fraud and financial crime in real time. Its customers include banks and other financial institutions, payment companies and digital businesses. The company was founded in 2013, is privately held and headquartered in Mountain View, California, with 51–200 employees. It recruits in the United States, Japan and Canada. The platform runs on Java and Python services across AWS and GCP, orchestrated with Kubernetes.
DataVisor runs Java and Python with Spring and Hibernate, streaming and storage on Kafka, Flink, Spark, Cassandra and HBase, ML on PyTorch, TensorFlow and scikit-learn, and AWS, GCP and Kubernetes.
DataVisor is headquartered in Mountain View, California, and also hires in Japan and Canada.
Job posts point to a real-time unsupervised ML platform, a next-generation machine learning platform, distributed streaming and database systems, and Salesforce integration with financial systems.
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DataVisor'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.