Ralph x Angus: The Volpara Health Top 10

Turning deep science into a globally-scaled health technology is not about hype — it’s about disciplined execution.

This interview distills the top lessons from Volpara founder Ralph Highnam in conversation with Angus Blair (GP, Outset Ventures) focused on what deep-tech founders must get right: data standardisation, early clinical validation, go-to-market strategy, regulatory sequencing, capital strategy, and sustainable engineering culture.

These insights apply well beyond breast imaging; they are a practical blueprint for anyone building in medtech, diagnostics, AI-in-healthcare, or research-driven startups.

1. The Origin: Technical Work Only Matters If You Build the Company Around It

Angus:

Where did the original idea come from, and what made you commit to actually building something around it?

Ralph:

“I was very good at maths and computing and stuff like that and I wanted to do a PhD because I didn't know what else that I wanted to do. So I thought, I'll do a PhD. But I didn't really even know what research was back then. I was poking around. There was all kinds of boring crap. Then I met this guy, Professor Sir Mike Brady, and he said his mother-in-law had just been diagnosed with late-stage breast cancer despite being screened, and he suggested we could improve screening using artificial intelligence. That kind of conversation sparked me. It was like, okay, this uses all my maths and computing, and I get to learn all about the breast — how the breast works, physiology, breast cancer. We tried to commercialise it in 1999 and it was just too early, but we returned to it in 2009 when we felt we had a duty to bring it to market due to clinical evidence building up. We choose the start-up route because you need complete belief to take it forward.”

Takeaway:

The technical spark only matters if someone decides it must exist in the world — and is willing to carry it.

2. Don’t Wait for Perfect Data — Start Independent Testing Early

Angus:

How did you get from the idea to something validated enough for FDA and early customers?

Ralph:

“We needed to come up an AI algorithm for breast density measurement from X rays. We needed to start testing it and because of our backgrounds we decided early on to get the algorithm out for independent validation by world-leading researchers. There’s risk involved in that, early algorithms often have issues, but with trusted but independent partners you can iterate the algorithm quickly to get to something FDA-ready. You have to really curtail that perfectionist angle.”

Takeaway:

External partners will break your assumptions faster than internal experiments. That’s the point.

3. Build the Product With Clinicians, Not For Them

Angus:

What shifted once you started seeing real clinic usage?

Ralph:

“We installed it into several beta sites. Some of them complete disasters (for various reasons). Most of them were fantastic. We learned a lot. We learned customer service. They said, ‘Don’t take it out. We love it.’ They said, ‘With your scorecards, we can talk to the women while they’re still at the clinic.’”

Takeaway:

Real workflow is the fastest teacher. It shows you what actually drives clinical and economic value.

4. Balancing Direct Sales and Distributors Is Not Optional

Angus:

You’ve said distribution mistakes are common. What’s the core rule?

Ralph:

“Never, ever go exclusive. Always have the ability to sell direct. They wanted exclusivity. We said no way. Distributors aren’t going to be able to sell early deep-tech, they like an easy-life. You have to get out there and do it yourself.”

Takeaway:

Education-heavy, category-creating products cannot be handed off to a channel. You need your own voice & ears in the market.

5. Mission Alignment Isn’t a Slogan — It Changes Who Shows Up

Angus:

Volpara seemed unusually mission-driven. What did that do inside the company?

Ralph:

“Everyone in the company had a sister or someone or friend getting breast cancer and then they were all getting breast cancer very early. We ended up changing the company’s slogan to saving families from cancer. That really resonated with everyone, investors, staff. It helped pull investors. We would say, come and save beautiful people.”

Takeaway:

Real mission changes hiring, retention, and who invests in you.

6. SaaS in Medtech: Painful Early, a Superpower Later

Angus:

What did the SaaS transition feel like internally?

Ralph:

“People didn’t believe we could switch to SaaS. It slowed stuff at the start and was painful. But then we really liked SaaS. It made you really listen to customers because you were so concerned about churn. New X ray machines are coming out. They change, the algorithms need to change quickly. You can’t do that unless you’re in the cloud.”

Takeaway:

SaaS forces deeper customer understanding and lets you adapt when hardware or standards shift.

7. Avoid the ‘Reimbursement First’ Trap

Angus:

You didn’t follow the usual reimbursement-first playbook. Why?

Ralph:

“We never went for reimbursement in the US. We always argued on increased revenues, and that we could reduce your costs. In New Zealand investors seem to want stuff that has a clear FDA pathway and clear reimbursement. But if that’s all clear, then someone else has already done it, and you’re not changing the world. If it’s good for the patient the regulatory & financial side will fit in.”

Takeaway:

If you create real clinical value and you understand the economics of the site, a viable business model often exists without needing formal reimbursement.

8. Engineering Pace: New Zealand’s Advantage Is Sustainable Output

Angus:

You’ve said NZ engineering culture helped Volpara. What did that look like?

Ralph:

“Everyone used to work at 9 to 5. That made me a bit mad every now & then. But we saw US companies spend 50 or 60 million and burn out. I really believe New Zealand’s got an advantage in sustainable, high-quality engineering. Don’t rush it. Have patient investors. That’s one of the reasons we ended up winning, it’s a long game”.

Takeaway:

Consistent, sane engineering beats burnout-driven heroics in deep tech.

9. Keep the Structure Clean or It Will Bite You Later

Angus:

You’ve noted the desire for clean company structures?

Ralph:

“There’s enough complexity in the world without your company structure being messy. You don’t want baggage hanging around, like various different classes of shares and weird share options. We applied that all the way through with Volpara and that ultimately led to a clean entrance onto the public stock exchange (ASX) in 2016.

Takeaway:

Complex structures and dirty cap tables slow everything: raising, partnerships, exits, hiring, and trust.

10. Hold Your Technical Belief Through Market Noise

Angus:

What kept you from switching to end-to-end deep learning when it became fashionable?

Ralph:

“Our core beliefs got seriously challenged by the deep learning tidal wave of noise. But we always believed the way we were doing AI was scientifically correct and would win in the long run by being best for patients. You get these periods of noise. But keep that core belief and always go back to that and challenge yourself.”

Takeaway:

Hype cycles don’t change physics. If your architecture is grounded in the real science, hold your line unless evidence tells you otherwise.