Findable

Created by team dhridhata on July 09, 2026
Unicorn Track

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.

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