Filter social posts missing alt text; auto-generate readable image text

Many content creators, community managers, and brand compliance teams struggle with social posts that lack alt text; an estimated 500 million active creators produce billions of images and most platforms do not provide practical tools to surface or remediate missing descriptions. The consequence is reduced reach for visually impaired audiences, poorer discoverability, and growing legal and reputational risk as accessibility enforcement tightens. You could build a tool that scans feeds and CMS content to flag images without alt text, auto-generates concise, human-readable descriptions using modern vision and OCR models combined with caption-context, and provides an editable, human-in-the-loop workflow before publishing. Deliverables would include a browser extension for creators, platform integrations and APIs for brands, and an enterprise dashboard for compliance reporting, monetized via a $16/year creator tier plus higher-priced enterprise plans. This market is attractive now: at $16/year across 500 million creators the addressable market is roughly $8.0B, and internal metrics (Market Score 92/100, Revenue Potential 84/100) reflect strong demand. Technically feasible advances in AI vision and OCR, increasing ADA/EU regulatory pressure, and platform fatigue among community managers make automated-but-editable accessibility remediation commercially timely. To stand out you must focus on quality and trust—contextual descriptions that combine OCR, captions and page metadata, transparent confidence scores, and lightweight human review will reduce inaccuracies and liability. The main challenges are integration friction with closed platforms, imperfect model outputs that require moderation, and willingness-to-pay by creators; strengths include a platform-agnostic approach, clear enterprise compliance features, and a hybrid consumer-plus-enterprise revenue path.