Easier Bets to Get Early Customer Validation and VC Attention
The article discusses the challenges of achieving scale in the Enterprise AI sector, emphasizing the need for substantial resources and a strong network. It highlights that VCs prioritize user adoption and customer validation, which can be difficult for startups to secure early on. The author suggests that personalized AI solutions and smaller SaaS products may offer better opportunities for early revenue and VC interest.
- ▪Achieving scale in the Enterprise AI space requires a large team and solid funding.
- ▪VCs look for user adoption and customer validation, which can take significant time to establish.
- ▪Startups may find it easier to gain traction with personalized AI agents and smaller SaaS products.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3810189) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Anant Posted on May 24 Easier Bets to Get Early Customer Validation and VC Attention There is not much of scale to be achieved in the Enterprise AI space unless you have a big team, a solid funding pipeline and a large multi-capability platform. Most AI work on the B2B large organization side is going to be building services, data products, APIs and integrating AI agents. From my experience, what VCs look for is user adoption/ customer validation.
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