Normalize and refactor code to remove AI-authorship fingerprints and stylistic signals

Normalize and refactor code to remove AI-authorship fingerprints and stylistic signals targets a $2.1B = 700K software teams × $3K ACV total addressable market with medium saturation and a year-over-year growth rate of 15% YoY — developer tooling and code-quality markets have been growing with cloud-native adoption and AI-assisted development (industry estimates aggregated from tooling vendor reports).

Key trends driving demand: AI-assisted coding adoption is rising — as more teams use code generation, demand grows for tools that manage the downstream operational and policy impacts.; Policy and community-driven bans or heuristics against AI-generated content are proliferating — this creates an immediate need for remediation tooling.; Shift-left and CI enforcement trends mean teams prefer automated fixes in pipelines rather than manual rework during code review, boosting demand for automated sanitization.; Open-source and supply-chain security focus has primed buyers to accept additional automated code checks, making new checkers (like fingerprint sanitizers) more adoptable..