Prevent LLM training/usage on shared code — license + enforcement service

Prevent LLM training/usage on shared code — license + enforcement service targets a $9.0B = 3.0M potential customers (open-source authors + orgs publishing code) x $3K ACV total addressable market with low saturation and a year-over-year growth rate of 30% (enterprise compliance spend + AI governance).

Key trends driving demand: AI-training-provenance -- enterprises and regulators demand traceability of training data and contractual constraints on model data sources, creating demand for data-level licenses and provenance tooling.; Legal-litigation-risk -- high-profile lawsuits against model trainers raise liability and insurance costs, motivating preventative licensing and monitoring.; Developer-reputational-concerns -- creators are increasingly unwilling to have work harvested for LLMs without consent, increasing opt-in/opt-out market.; Platform responsibility pressure -- code hosts and cloud providers face pressure to respect content license preferences and may integrate enforcement tooling..