Automated red-teaming sandbox that finds LLM prompt jailbreaks & leaks

Automated red-teaming sandbox that finds LLM prompt jailbreaks & leaks targets a $3.6B = 200,000 businesses deploying LLM features × $18K ACV for safety/red-teaming tooling total addressable market with medium saturation and a year-over-year growth rate of 25% — estimated combined growth for AI security and LLM tooling driven by enterprise adoption and regulatory focus (sources: Gartner AI security insights 2024, McKinsey AI adoption trends).

Key trends driving demand: Rapid LLM adoption across SaaS and consumer apps — this creates continuous demand for safety and leakage testing as more products integrate generative features.; Regulatory and compliance pressure — governments and enterprises are increasingly asking for auditable testing and evidence that AI systems are safe, creating demand for reproducible red-teaming.; Shift from manual red-team engagements to automated, CI-integrated safety tests — teams want programmatic gating and regression testing for prompt changes..