Automate removing repeated words and batch text cleanup with smart NLP

Automate removing repeated words and batch text cleanup with smart NLP targets a $12.0B = 100M knowledge workers x $120 avg annual spend on writing/editing tools total addressable market with medium saturation and a year-over-year growth rate of 14% (writing/productivity tools market).

Key trends driving demand: Transformer efficiency -- smaller, faster NLP models enable real-time, local text cleaning in editors and CI pipelines.; Editor extensibility -- growing plugin ecosystems (VSCode, JetBrains) make distribution and adoption of niche tooling trivial.; Content velocity -- more companies produce continuous content, increasing demand for automated quality gates and batch fixes.; Enterprise compliance & localization -- teams need deterministic text fixes across translations and legal copy, creating demand for controlled automated edits..