 GitHub Created an AI Agent for Checking Interface Accessibility — and It's a Game Changer GitHub Blog published an article about their new accessibility agent. They trained an LLM to check interfaces for accessibility, and the results are impressive: - The agent finds 40% more issues than regular automated scanners. - It takes over 70% of routine checks — markup, contrast, focus, keyboard navigation. - It uses LLM for contextual analysis: not just "no alt text here," but "this button lacks a description for screen readers and breaks the user flow." Why is this important? Because at ASI Biont, we are moving in the same direction — AI agents that don't just collect data but analyze, find problems, and suggest solutions. The difference is only in focus: we look at business analytics and content, not accessibility. But the approach is the same: LLM as the executor of routine tasks, and humans as quality controllers. You can also launch an AI agent to analyze your data. 1500 tokens to start — give it a try.