DataStealth is a data protection platform designed to secure data across on-premises, legacy, mainframe, hybrid, cloud, and SaaS environments without requiring application rewrites, migrations, or agent deployments. It operates as an inline network layer, sitting between applications and data stores to enforce protection controls in real time as data flows. Deployment options include gateway, reverse proxy, sidecar, and datastore proxy configurations. Core protection mechanisms include tokenization, data masking, and encryption, applied automatically to data in motion across databases, files, APIs, SaaS platforms, event streams, and data warehouses — including legacy systems such as mainframes and DB2. DataStealth performs agentless, real-time data discovery and classification across structured and unstructured data, including shadow IT and dark data repositories. Discovered sensitive data is subject to inline policy enforcement with role-based reveal controls rather than alert-only responses. Unified policies can be applied consistently across on-premises, cloud, multi-cloud, and hybrid architectures from a single platform, replacing multiple point tools for discovery, classification, protection, and compliance reporting. The platform also extends data protection to AI pipelines, LLM workflows, and API-based data flows, intercepting sensitive data before it reaches AI systems. DataStealth is positioned as a direct alternative to Varonis for organizations that need to retain on-premises or hybrid infrastructure rather than migrating to a SaaS-only model.