Preventing employees from leaking sensitive company data into public LLMs (real-time DLP for chatbots)

Preventing employees from leaking sensitive company data into public LLMs (real-time DLP for chatbots) targets a $8.4B = 280k enterprises × $30K ACV (enterprise DLP and security-adjacent budgets focused on AI safety and controls) total addressable market with medium saturation and a year-over-year growth rate of 20% YoY (driven by enterprise security software growth plus new spend to secure AI usage; based on industry reports and increased AI-specific security line items).

Key trends driving demand: Rapid LLM adoption — companies are adopting chatbots and LLM APIs for knowledge work, increasing the surface area for accidental data exfiltration and creating demand for targeted controls.; Security-first AI governance — security and compliance teams are prioritizing solutions that allow safe AI use rather than blanket bans, creating procurement opportunities.; Shift to API and conversational telemetry — enterprises want inline, low-latency inspection at the API and chat layer, which old DLP systems do not natively provide.; Hybrid deployment preference — regulated customers demand on-prem or VPC-hosted options for any product that touches sensitive content, favoring vendors that support hybrid architectures..