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Prexist – AI-powered search for products (now 3x faster with Exa AI)

Hacker News

Prexist – AI-powered search for products (now 3x faster with Exa AI)

Hey HN I built Prexist, an AI-powered tool that helps founders, PMs, and VCs quickly find out if their startup idea already exists, across 8 major platforms like Product Hunt, YC, GitHub, Crunchbase, and the App Stores. Until recently, running searches across all these platforms in parallel took ~60 seconds. We’ve just integrated Exa AI for search orchestration, and it’s now 3× faster while returning more relevant, semantically matched results. What it does: - Uses AI to understand your product idea and generate smart search queries - Searches 8 discovery and innovation platforms simultaneously - Lets you generate and share reports with a single link Use cases: - Founders validating product ideas - Product teams doing competitor scans - VCs doing due diligence on new investments Would love your feedback, especially from anyone who’s tried automating multi-platform searches. Happy to answer technical questions or talk about how we can improve the product further. - Team Prexist

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: new, single · Missing: mac, agents, macos
94%94% 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: para · Missing: supports, reddit linkedin, podcasting
83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, ide, io · Missing: https docs, excited, just released
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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