Aaditya Acharya@aads16

Search is shifting from ranked links to synthesized answers. When users ask ChatGPT, Perplexity, Claude, or Google AI Overviews a question, they get a single authoritative response and the websites that power that response are chosen by AI crawlers on very different criteria than the ones Google has used for two decades. Findable audits any public URL the way AI systems actually see it: it fetches both rendered and raw HTML to detect JS-gating, checks robots.txt for per-bot access rules, scores schema.org and llms.txt markup, evaluates E-E-A-T signals and citation worthiness, and maps how well the page's entities align with knowledge graphs all in parallel via four specialized AI agents running on Gemma models served through vLLM on AMD ROCm hardware. The output is a concrete 0–100 AI Readiness Score with per-category breakdowns (Crawlability, Content Signal, Structured Data, Entity & Topic), an estimated before/after visibility profile for each major AI bot, and a prioritized list of actionable fixes streamed live to a real-time SSE dashboard and exportable as PDF or Markdown. The project sits at the intersection of SEO tooling and the emerging AEO discipline, a market projected to grow from $160.9M in 2026 to $4.1B by 2035 (43.4% CAGR), with over $200M in disclosed venture funding in the category as of early 2026.

To participate in the hackathon, simply click Sign up with AMD. If you are not already a member of the AMD AI Developer Program (ADP), you will need to create an account. ADP members can access AI tutorials, experts, and community support. In addition, new members can claim a free month of DeepLearning.ai pro, $100 in AMD GPU cloud credits, and $50 in Fireworks AI API credits. All hackathon participants will receive on hackathon launch additional compute and API credits for their projects. Ready to build what's next on AMD? Sign up with AMD below to secure your spot.