Bad non‑English captions for South‑Asian creators — AI captions + motion graphics

South-Asian short-video creators publishing in Hindi, Bengali, Tamil, Telugu, Urdu and dozens of local dialects routinely get poor automated captions: mistranscriptions, wrong transliteration, and captions that break visual composition. This harms discoverability and watch-time for individual creators and small studios — a problem felt across the estimated 300M global video creators and a concentrated cohort of tens of millions of creators and viewers in South Asia. You could build an AI-driven captioning and motion-graphics tool that combines multilingual ASR tuned for South-Asian languages, a lightweight mobile editor with human-in-the-loop correction, and culturally aware motion-graphic templates that improve readability and retention. The market is attractive now: a ~$9.0B addressable market (300M creators x $30/year), a market score of 92/100 and revenue potential 88/100, driven by a short-video boom, rapid improvements in multilingual ASR/LLMs, and platform incentives that reward captioned content in low-English-proficiency markets. To stand out, focus on language-specific acoustic models for low-resource dialects, prebuilt motion-graphics that match regional aesthetics, tight export flows to Reels/Shorts formats, and an optional quality-review marketplace for creators who need broadcast-grade captions; competition is medium, so localization and execution will determine win rate. Strengths are a large TAM and clear creator ROI; challenges are ASR accuracy on noisy user-generated audio, the cost of labeling and human QC, and platform integration — start with a few high-volume languages and creator partnerships to validate unit economics before scaling.