Emoji picker inaccessible: announce list info & position count

Many websites and web apps use custom emoji pickers but fail to provide basic screen‑reader context such as the list category, total items, and the current position, leaving users with assistive technology unsure what changed as they navigate — this is a practical accessibility gap faced by frontend engineers, product teams, and accessibility auditors across an estimated 20 million sites. The consequence is measurable: organizations are spending on average $360 per site per year on accessibility tools and remediation (a $7.2B addressable market), and emoji pickers are a common, low‑cost point of failure in audits and procurement reviews. A focused product could ship a drop‑in library and developer tools that detect emoji picker patterns and automatically apply ARIA best practices (aria-posinset/aria-setsize, aria-live announcements, aria-activedescendant and listbox roles), plus Storybook components, automated tests, and optional LLM‑assisted code fixes or pull requests for legacy code. You can offer a free OSS core for adoption and paid enterprise plugins and CI integrations that produce audit reports and remediation PRs, aligning with the component‑first workflows used by modern teams. This is an attractive moment: regulatory enforcement and procurement rules are tightening (more audits and litigation), component reuse is rising in React/Storybook workflows, and AI tools lower the cost of bulk remediation — the market score here is high (90/100) and revenue potential solid (82/100) with medium competition. The product’s strengths are clear technical depth and developer ergonomics, but challenges include cross‑screen‑reader and browser inconsistencies, mobile OS picker differences, and the need to build trust with enterprise security and procurement teams; success will depend on rigorous testing, clear compliance artifacts, and easy integration paths.