CompanyGPT – build targeted company list using natural language

Hacker News

I’m Abhilash, one of founders of CompanyGPT. Our mission is simple - let investors and sales teams build list of companies using plain English Example: "Find companies building video editing tools using generative AI, that have raised more than $2M, that have headcount growing more than 20%" — Why CompanyGPT? Ever tried finding companies based on the description of what they do? Eg: "Companies building robots for fighting forest fire" Google search returns content marketing articles around forest fire and climate change Crunchbase doesn't have a category for these companies Linkedin categorizes them as "Forestry and Logging" Then the only other option is to manually search through 100s of companies and spend 10 hours. This is not how it should be. CompanyGPT changes this. We track 1M+ companies and help let you easily list the companies that match your description using our fine tuned AI models. — Who is it for and how does CompanyGPT help? 1. VCs and PE Investors : thematic research to screening 2. Sales and growth teams: lead generation 3. Strategy and revenue teams : GTM insights 4. Research analysts: performing market research Free trial: https://crustdata.com/company_gpt Product hunt launch: https://www.producthunt.com/posts/companygpt

Visit product View on Hacker NewsAug 25, 2023

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

85%85% 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 · Missing: supports, reddit linkedin, podcasting

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video, google · Missing: mobile apps, ios, personal

63%63% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: revenue, growth · Missing: arr, mrr, profit

28%28% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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