As artificial intelligence becomes a buzzword in nearly every healthcare startup pitch, investors are finding it increasingly challenging to distinguish which ones are actually worth the hype.
That’s why, during a Thursday panel discussion among venture capitalists at the MedCity INVEST Digital Health conference in Dallas, this question was posed: What metrics do you want to see founders highlighting more often when they’re pitching, and what is one red flag that makes you question the validity of their technology? The session was moderated by Neil Patel, head of ventures at Redesign Health.
Here is what they had to say:
What founders should be highlighting
For Maddie Hilal, investor at Oak HC/FT, it’s important that startups have strong net revenue retention, which measures a company’s ability to retain revenue from existing customers.
“If we don’t necessarily have visibility into those hard [profit and loss] impact proof points, but your existing customer base is growing their contracts, clearly they’re excited,” she said. “They’re seeing the value.”
Another investor looks for companies with high quality data.
“If you have better, higher quality data, you can solve problems in a much better fashion, [with] higher predictability of models. I think we look for that. What’s that proprietary data set? What are you trained on? Who and in which environment has this been deployed?” said Rohit Nuwal, partner at TELUS Global Ventures.
Vickram Pradhan, vice president of Sopris Capital, wants to see AI startups with a good clinical impact.
“People are asking about clinical impact in a way that they weren’t asking maybe five years ago,” he said on the panel. “I think the reason for that is that some of the reimbursement and financial and payment mechanisms in healthcare are a bit of a black box. … But if you know what you’re doing is having a really meaningful clinical impact, that’s a pretty good foundation to know that that’s going to have value, and someone’s going to want to pay for that.”
AI red flags
Many healthcare startups will use the AI buzzwords in their pitch decks, but don’t back up their claims with strong data and validating metrics, according to Hilal. This is a major red flag, she said.
Nuwal echoed Hilal’s comments.
“I think there’s a lot of AI being thrown around where it’s essentially largely a machine learning problem that people are trying to solve,” he said. “I don’t blame them, founders are doing a tough job raising money in this environment, so you need to play the game a little bit. But I think just being authentic about what problem you’re solving goes a long way.”
For Pradhan, a red flag is having “squishy” revenue metrics. It’s important for companies to be realistic with investors.
“I think it’s very common to see today, especially with some of these AI companies that are doing a lot of pilots talking about, ‘We’ve got 10 million of contracted revenue.’ And then when you kind of go a layer or two deeper, it’s like, ‘Oh that’s actually what it will look like in year three.’ … It just makes it a little bit more challenging to arrive at a sound basis of truth,” he said.
