AI-powered cyber risk quantification and exposure management platform
Balbix ingests security and IT data across 150+ systems to surface cyber exposures and quantify risk in business terms. The tech stack—TensorFlow, PyTorch, Kafka, Spark, Flink, Cassandra, Elasticsearch, and a lakehouse architecture—reflects a machine-learning and data-pipeline-heavy engineering operation built to handle petabyte-scale cybersecurity datasets. Current hiring is concentrated in senior and principal engineering roles, with no new postings in the last 30 days, suggesting a mature platform in stabilization rather than feature expansion.
Notable leadership hires: Technical Lead
Balbix is a cyber risk and exposure management platform for enterprises. The product unifies data from 150+ security and IT systems into a consolidated view, then applies machine learning to prioritize exposures by exploitability, blast radius, and business impact. It also quantifies cyber risk in financial terms to support board and insurance conversations. The platform serves CISOs and vulnerability management leaders at global enterprises across cloud, on-premises, and hybrid environments. Founded in 2015 and based in San Jose, the company operates with a small, engineering-led team focused on backend systems, data pipelines, and risk modeling.
Balbix uses TensorFlow and PyTorch for machine learning, Python and Java for core services, PostgreSQL and MongoDB for transactional data, Cassandra and Redis for distributed caching, Kafka and Spark for data pipelines, Elasticsearch for search, and AWS/Azure/GCP for cloud infrastructure.
Balbix is headquartered in San Jose, CA. The company hires engineers and staff in the United States and India.
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Balbix'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.