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 the importance of early customer validation for attracting venture capital, which can be difficult for startups due to limited funding. The author suggests that personalized AI solutions and smaller SaaS products may be more viable for generating early revenue and securing VC interest.
- ▪Achieving scale in Enterprise AI requires a large team and solid funding.
- ▪Early customer validation is crucial for attracting venture capital.
- ▪Startups often struggle to obtain the resources needed for customer validation.
Opening excerpt (first ~120 words) tap to expand
There is not much of scale to be achieved in theEnterprise 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. Now, that typically takes a year or so depending how strong your network is or whether you have a dedicated sales and marketing org within. Most startups do no have that kind of money or resource, so getting customer validation early is difficult.Personalized AI agents, recruitment AI, domain specific GPTs, smaller SaaS etc.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Ycombinator.