AI-native data loss prevention platform for SaaS and generative AI security
Nightfall AI operates an agentic data loss prevention platform built on Python, Go, and ML infrastructure (PyTorch, spaCy, Transformers, LSTM). The stack reveals a company scaling AI inference and real-time detection at volume—Kafka + Redis + Cassandra handle streaming data, while projects target auto-scaling services and detection-accuracy improvements. Hiring is engineering-heavy (8 engineers vs. 6 sales) with senior and lead-level concentration, indicating they are building detection models and platform resilience rather than pure sales-driven expansion.
Nightfall AI provides an all-in-one data loss prevention platform designed for security teams at enterprises and mid-market firms. The product combines cloud DLP, data discovery and classification, and AI detection models to prevent data exfiltration across SaaS applications, endpoints, and generative AI systems. Core capabilities include stopping unauthorized data sharing, revoking improper access, blocking shadow AI data leakage, and coaching end-users on risky behavior. Founded in 2018 and headquartered in San Francisco, Nightfall operates with 51–200 employees and is actively hiring across engineering and sales in the United States and India.
Nightfall uses Python, Go, C++, Java for core services; PyTorch, spaCy, Transformer, and LSTM for ML detection; Kafka, Redis, PostgreSQL, Cassandra, and Hadoop for data infrastructure; and integrates with Gmail, Slack, Salesforce, VMware Workspace ONE, and CASB/SOAR platforms.
Nightfall is actively hiring in the United States and India.
Nightfall AI'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.