If you've ever wanted to answer a question like "which YC startups from the last two batches are building developer tools?" you know the only real option used to be manually browsing YC's directory page by page. ExploreYC turns that kind of research into a query: it pulls together startup and funding information from Y Combinator, a16z, and Product Hunt into one place, and lets you access it either through a web interface or a REST API. ExploreYC is a free API and database platform aggregating startup ecosystem data — company profiles, funding signals, and launch information — from YC, a16z-backed companies, and Product Hunt. It's built for developers, researchers, and analysts who want to query this data programmatically rather than scrape each source separately: think building a dashboard of a specific YC batch, tracking a16z portfolio activity, or feeding startup data into another tool. There's no paid tier currently — the whole thing is free to use.
| # | Tool | Best for | Price |
|---|---|---|---|
| 1 | Équipes data mid-market et enterprise, responsables data/analytics, équipes IA voulant démocratiser l'accès aux données | — | |
| 2 | Équipes trading (matières premières/énergie), supply chain, cabinets de conseil, e-commerce/retail, entreprises | — | |
| 3 | Développeurs et équipes construisant des agents IA ou des pipelines de données qui ont besoin d'extraire des données web structurées sans gérer leur propre infrastructure de scraping | — | |
| 4 | Équipes produit d'entreprises B2B software voulant du feedback utilisateur sans surcharge RGPD | — | |
| 5 | Équipes marketing, produit, insights et agences voulant valider des idées rapidement avant une étude complète | — | |
| 6 | Investisseurs individuels et professionnels de la finance voulant des tableaux de bord sans compétences tableur/terminal | — | |
| 7 | Analystes et petites équipes voulant explorer de gros volumes de données sans monter un data warehouse | — | |
| 8 | Chefs de produit, équipes product ops, design et agents IA dans des entreprises SaaS voulant un contexte client unifié et à jour | — | |
| 9 | Équipes marketing, partenariats et R&D produit dans l'e-commerce voulant une lecture fiable et vérifiée du sentiment public en ligne | — | |
| 10 | Petites entreprises et marketeurs solo qui trouvent Ahrefs/Semrush trop chers | — | |
| 11 | Technical and non-technical teams who want natural-language answers from their data warehouse | — | |
| 12 | SMBs and enterprises with lean data teams (finance, marketing, ops) needing pipelines without a dedicated data engineer | — |
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