Automated vetting and change-control for AI-generated code in SDLC

Automated vetting and change-control for AI-generated code in SDLC targets a $10.8B = 2M engineering teams × $5.4K ACV each (covers code vetting, CI/CD policy, and SRE integrations across mid-market + enterprise) total addressable market with medium saturation and a year-over-year growth rate of 15% YoY — developer tooling and application security budgets have been growing mid-teens annually (sources: Forrester/IDC 2023-2024 estimates).

Key trends driving demand: Trend — Rapid adoption of AI coding assistants is increasing the volume of machine-generated diffs that require governance, creating immediate demand for vetting solutions.; Trend — Security and procurement teams are demanding auditability and policy enforcement for AI outputs, which creates enterprise buying motions tied to compliance.; Trend — CI/CD pipelines and observability systems are mature and extensible, enabling vendors to insert policy and vetting gates without large engineering changes.; Trend — Shift-left security and developer-first tools continue to win budgets; embedding vetting into the developer flow reduces friction for adoption..