5 (Spooky) Secrets to mastering AI diligence
October 31, 2024
Happy Halloween! Understandably, you're fundraising to help your company grow. But are you making these 5 common mistakes when selling, positioning, or pitching your product?
Having reviewed 200+ startup pitches, websites, and pitch decks and delved into Data Rooms and implementation details, here are the top 5 orange/red flags I've seen again and again.
Not Passing the AI Litmus Test
"If you [removed] references to AI in your pitch deck, is this still a good business?" – NFX’s AI Litmus Test
While it seems that everyone else is an AI startup and that you need AI in your MVP to fundraise, customers don’t pay for AI; they pay for solutions to their painful problems!
How many of us are choosing to pay for the algorithms powering Google, Netflix, and Uber? …We just want great search results, entertaining movies, and the ability to reach our destination — we don't care how the company delivers that promise!
Not Developing an End-to-End Solution
Does your solution tie end-to-end from customer habits to solving their pain point with your product? The discussions around this will include:
Setting realistic expectations about what does and doesn’t currently exist in your product – and what milestones you’re looking to hit with the fundraise
Onboarding experience and workflow for your customers, including what they can do themselves, what you can support them with, and what they need to outsource to a third-party
(If applicable) How personalization – and AI (re)training – comes in
Not Selling VCs on the Team
VCs will be the first to tell you that most ideas are not new! How are you the best team to solve this for your customers?
Have you lived in your customers’ shoes and understand their pain first-hand?
Have you invented the workflow/device/algorithm that’s key to solving the pain point?
Does your team, which includes advisors and/or contractors, cover the required business, industry, technical, and, if applicable, AI and/or FDA expertise to pull this off?
Why can’t someone else pitch this idea to the same VC?
Showcase this!
Not Understanding the Market
"The #1 company-killer is lack of market." – Marc Andreesen
While the notion of "market" may mean different things to different people, when I evaluate start-ups, I think about the following:
Is the GTM strategy focused on 1 very specific ICP for whom you solve 1 very specific problem – or are you trying to be all things to all people?
Is the product venture scalable?
For example, if an investor gives you $10M for 10% of your company and your exit is $100M, they break even. Actually, they lost money when adjusted for inflation!
How can your product become the next unicorn, with a $1B+ exit, so investors get multiples of their money back?
Does the monetization strategy make sense, from attracting repeat paying customers to aligning incentives between your customers and the product?
Is an exit possible within the fund’s lifecycle?
Not Knowing the Costs
Especially in diligence, many AI-driven start-ups aren’t able to talk about their:
Current cloud computing costs, even if you use cloud credits to do so!
Depending on the volume of data you’re storing and processing and the nature of your algorithms, this may be $10K+/month, which will heavily impact your runway! Be ready to discuss this!
Current and future costs related to hiring the team to help you pull off the milestones you’re promising your customers and investors.
I can’t tell you how often I see start-ups that pitch the world with their product, including inventing and implementing state-of-the-art AI algorithms that surpass FAANG/MAMAA, only to budget an intern or a part-time offshore contractor for this!
Now that you know the top 5 mistakes others make, you’re more prepared to fundraise – and to close the round! Good luck!
If you’d like me to review your pitch deck and website, or the pitch deck, website, the Data Room, and product, as I would for an investor, please schedule your flat-fee session via these Calendly links.
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