Grow and Monitor Your AI Search Traffic

Hacker News

Hi HN, I’ve been working on Spiderseek, a platform to help track and grow website visibility in AI-powered search engines (e.g. Perplexity, ChatGPT, and other agents). Traditional SEO tools are expensive and focused on Google-style search. I wanted something lightweight and AI-first, so I built Spiderseek: AI Research – Explore domains and keywords to uncover new opportunities. AI Analytics – See traffic, crawl activity, and page metrics, plus insights from AI agents. Content Submission – Get content indexed instantly in major AI agents. Rankings – Browse the top 1000 domains sorted by citations and sources. It’s very early, but live and priced at $1/month while I grow the database and features. I’d love feedback from the HN community on: How useful this data feels. What additional features you’d want. Which AI Search Engine Coverage is most important to you (e.g ChatGPT vs Copilot Vs Gemini) https://www.spiderseek.com Thanks! Andy

Visit product View on Hacker NewsSep 22, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, google · Missing: mac, macos, cursor

92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, google · Missing: mobile apps, ios, personal

49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: plus, platform · Missing: intuitive, reviews, host

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released

31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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