Data privacy vault and runtime controls for sensitive data and AI
Skyflow sells a privacy and data-control layer that sits between sensitive records and the apps, data platforms and AI models that consume them. A multi-cloud footprint (AWS, GCP, Azure) plus Go, Java and Kafka points to latency-sensitive infrastructure, while an even engineering-and-sales hiring mix and new territory work in Saudi Arabia show a company pushing enterprise outbound and Middle East expansion alongside core platform performance.
Skyflow is a privately held data security company founded in 2019 and headquartered in Palo Alto, California, with 51–200 employees. Its platform protects, governs and controls the use of sensitive data such as PII, PHI and payment data across datastores, applications, models and AI agents. It serves enterprises in financial services, healthcare, travel and hospitality, and retail. Hiring spans the United States, India and Saudi Arabia across engineering, sales and product.
Skyflow's stack includes Go, Java, Python and C++, running on AWS, GCP and Azure with Kubernetes, Terraform and Pulumi, plus Kafka, Snowflake, BigQuery, MongoDB and ML tools like PyTorch, MLflow and SageMaker.
Skyflow is hiring in the United States, India and Saudi Arabia, with hiring accelerating across engineering and sales and mostly at senior level.
Job posts point to privacy APIs and backend infrastructure for large-scale data workflows, low-latency high-throughput performance engineering, embedded OEM partnerships and Middle East territory development.
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Skyflow'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.