Alberto Rizzoli Podcast Transcript
Alberto Rizzoli joins host Brian Thomas on The Digital Executive Podcast.
Brian Thomas: Welcome to Coruzant Technologies Home of the Digital Executive Podcast. Do you work in emerging tech, working on something innovative? Maybe an entrepreneur? Apply to be a guest at www.coruzant.com/brand.
Welcome to The Digital Executive. Today’s guest is Alberto Rizzoli. Alberto Rizzoli is a serial entrepreneur and AI systems expert, best known as the co-founder and CEO of V7, a UK based company building AI to automate knowledge work.
At V7, Alberto helps enterprises like GE Healthcare, Merck, and Sony streamline their most document heavy and detail driven workflows. Turning unstructured data into structured insights that fuel efficiency and scale. His work focuses on practical AI that delivers measurable outcomes in high stakes environments, from healthcare to finance, to insurance where accuracy and compliance are non-negotiable.
Before V7, Alberto founded IPoly, a pioneering computer vision app that identified objects in real time to assist people who are blind or visually impaired. The technology scanned over 2 billion objects worldwide and was translated into 26 languages earning Alberto recognition from the President of Italy and multiple CES best of innovation awards.
Brian Thomas: Well, good afternoon, Alberto. Welcome to the show!
Alberto Rizzoli: Hey, Brian, great to be here. Thank you for having me.
Brian Thomas: Absolutely, my friend. I appreciate you making the time in London, England. I’m in Kansas City, so got a six hour difference today, but I appreciate you navigating the time zones. And Alberto, I’m gonna jump into your first question.
You built AI Poly to assist visually impaired users and now lead V7 to tackle enterprise AI workflows. What were the hardest lessons you learned in transitioning from a mission-driven consumer product to the B2B infrastructure platform, and how do they inform your decisions today?
Alberto Rizzoli: Yeah. So IPoly, my previous AI company that I started in 2015 was very mission-driven.
It was helping some of the least privileged people in society, which are people with total or almost total visual impairment. So the totally blind, effectively. And it was using AI to identify objects in real time from your phone without requiring an internet connection. So entirely using the processing power of smartphones available back in 2015, which were not very powerful at all.
Neither was AI. Very powerful, but it was a very mission-driven effort. And as mission-driven, V7 is today because its impact on the healthcare industry, on insurance. Actually leads to massive improvements in life. It feels less obvious because it IPoly would be an app that would get the users who tried it first time to be moved and sometimes moved to tears, which was incredible.
It had this really strong viral approach, and most importantly was a consumer app. So anyone could download it on their phone at the dinner table, test it out with their phone around and it would speak back at them saying, Hey, I see a plate of steak and I see a wine glass. And it would be really fun to do.
V7 on the other side has significantly higher impact. It was founded in in 2019 and it automates anything that we consider to be back office work. So all the paperwork processes that large companies need to do are now handled by V7 AI agents, and we’ve been able to manage hundreds of billions worth of, of transactions that would normally have to be done manually.
And paperwork that really have to be done manually. That ends up becoming a huge cost to society. 40% of our administrative of our cost in the healthcare system in the UK the NHS is administrative. It’s people that are not helping the patients on the ground. They’re not nurses, they’re not doctors, they’re not surgeons.
They are in the back office handling effectively the ineffective bureaucracy of that system. You need to develop a very strong sense of storytelling in order to inspire people to solve some of the most ugly and boring problems in society, and you also need to make it fun. So something that we focused a lot on in, in developing V7 is making the user experience of the product.
As fun and as intuitive as possible. So you feel like you’re orchestrating these automations as a designer of this workflow as opposed to doing the actual boring work that these automat are, that these automations, these AI agents eventually tackle. So the main lesson is if you’re building something B2B, you have to make it fun and you need a really good storytelling angle to it so that people are inspired by the mission behind it.
As much as B2B missions tend to be much more stale than consumer ones, especially ones in assistive technology like IPoly was.
Brian Thomas: Thank you so much. I appreciate that and love the backstory. Obviously you’re very much mission-driven. Your original business was to help people with disabilities serving consumers.
And now you’re doing the same thing with V7, working to help humanity in the healthcare space, leveraging the latest AI technology. But I also highlighted your good storytelling makes a difference and obviously making things fun. Always goes a long way, so I appreciate that. And Alberto V seven emphasizes combining human expertise with AI to deliver trustworthy ai.
How do you operationalize that in practice, especially in high regulated domains like healthcare, finance, so that clients feel confident in automation decisions?
Alberto Rizzoli: Effectively, AI knows a lot about everything, but it often doesn’t know how to do your job or the parts of your job that you want to automate well enough for you to actually trust it.
V7 allows you to show an AI the step-by-step process of anything that you do, and it lets you explain to it how to handle any edge case for it. That ultimately you’re creating your own AI agents that are almost like your own employees, that are able to tackle these in a way that is reliable.
And for anything that is an edge case, they can come to you and ask you for questions and clarifications. The step-by-step development of a workflow is essential to making AI actually feel like something you can rely on in healthcare, in health insurance. There, there’s a lot, there’s no margin for error really.
And there’s also no tolerance for automation errors much lower. We’re much more forgiving if a human makes a clerical error. And there are many of them in especially regulated industries, but we’re very inflexible towards automation because it makes us feel like we’ve gone the cheap route.
We have therefore created a mistake that is systemic and it’s affecting people. And so it’s very important to develop software that can reach as high of an accuracy as possible and is reliable in the way that it discloses its errors. The way we do it in practice at P seven is that every decision that the AI makes and every piece of analysis is forced to be grounded in documented evidence.
That means that if an AI is making a decision based on. Someone’s policy or based on someone’s patient pathway or based on someone’s we, we also process mortgages, for example, which is a really high impact activity because it’s, it’s literally someone’s future on the line and their home.
It always needs to provide not just a source evidence as a link, but it needs to go into a document and find the exact statement and then highlight it with a box. So they can never hallucinate and it’s always giving you a traceable answer. And it’s also developed to not be overly optimistic about what it wants to tell you, to be very factual with the presentation that it gives you back and not to try and make the user happy like many ais do.
And to ask for help for anything that is subjective and requires a bit of a human opinion to it. And there, there’s a lot of technical detail that goes into this, but if you wanna learn more, V7labs.com is a great place to, to, to go check it out.
Brian Thomas: That’s awesome. Thank you.
And I agree with you, AI has come a long way. I think it still has a long ways to go and your platform, it aims to, stand out in the industry because your platform can follow specific job tasks and mimic day-to-day workflows. And your platform does go beyond automation. It actually looks.
To logically solve issues. And what I really liked Alberto, is it asked for help for anything that is really subjective or needs some clarification. I think that’s really important. And Alberto, when your platform is used in healthcare, pharma, or insurance settings, errors or biases can have real consequences.
What governance, validation, or oversight frameworks do you insist on inside V7? And how do you partner with clients to enforce them?
Alberto Rizzoli: Yeah. So, recently certifications have been a lot more streamlined for software companies. There’s things like ISO 27 0 0 1 and SOC two, and the, all these large checklist exercises that help you effectively know that the company that you’re dealing with, the vendor you’re dealing with, with AI has data security and integrity.
I think getting to know the people behind the software is quite important, knowing that they are not vibe coding their way through a piece of software, but actually building something incredibly robust. And often that’s quite hard when selecting an AI vendor. We often get asked whether any of the data that we process ends up being used to retrain models.
We get asked that almost all the time. It really shows that there’s a concern of data leakage. There’s a concern that AI will ultimately use your information to improve itself. And we absolutely don’t do that. However, there, there is still this this sense of, Hey, we are delegating everything to, to this AI can it, couldn’t it not just understand everything about our business and then effectively replace what we do.
We’ve decided not to take a stance of going after our customers, of course, but you know, they know their area best and we want to provide them with the infrastructure to develop agents that belong to them, prompts that belong to them, output data that belongs to them. And this was really important for us from the start because we can’t really have a, we’re all about trustworthy ai.
We can’t claim to be creating trustworthy AI if we ourselves, as the vendor, cannot be trusted with our customer’s data. So it’s a very sacred element of, of what we’re given. And a lot of AI selling is trust building, is making sure that the customer on the other side sees you as a partner for the long run and understands that we are here to help them build something incredible with AI.
Not to effectively be this this vacuum of data which has happened in the past with, with some software companies. And I think the we’re at the stretching limit of, of people’s patients with the information not being treated correctly.
Brian Thomas: Thank you and I really appreciate that.
A lot of things, nowadays are more streamlined, more efficient as far as those certifications, whether you’re hooking into an API, that sort of thing. I liked how you explained it is important to you that you build your trust with the customers, show them that you’re there to help and to be a long-term strategic partner.
I appreciate that. And Alberto, last question of the day, looking ahead maybe five, 10 years, how do you hope V7 and your work will change how we think about intelligence, knowledge work and human augmentation? What legacy do you want to leave? Not just in tech, but how we live with AI?
Alberto Rizzoli: Things are going to be wild in five years.
I think the rate of improvement of AI is slowing down a little bit, but there are still enough gains for us to capture, to see the world very much transformed. I, I think we will see more changes in the next five years than we have seen in the last 15 and even the last 15. You know, we didn’t have the smartphone at the time, so there’s been some really big changes.
And our legacy is in transforming what we consider to be work. We’ve created a society where after the industrial revolution, we’ve moved into big cities so that we could do this new we, we call it the tertiary sector in, in Italian. I’m not sure if it’s the same as in English, but its services or the service industry that, for example, the United States considers to be its biggest contributor to GDP is the new agrarian industry preindustrial revolution.
It will change significantly, but. It will not necessarily make things more or or less fun, it will remove, and I hope that V7 will remove all the bureaucracy that we’ve created in order to systemize the services industry, whether it’s legal services, insurance services financial services, and it will also reduce the margin of knowledge arbitrage to near zero.
Which means that our insurance policies should become cheaper because we no longer have all this administrative costs. Our public funds should be used more wisely because we have we have knowledge workers on tap. We have effectively the power of administering a budget as if we had unlimited time to spend on it, rather than having to rush through the allocation of funds, which often lead to painful mistakes and the mismanagement of taxes.
And the societal changes that we will see will first of all lead to a change in labor where we will have fewer individual contributors in the domain of knowledge work. So fewer paralegals, for example, or, or juniors, which is will, will kind of have a negative impact on young graduates. These young graduates will want to adapt to becoming workflow designers and AI designers effectively.
And it’s becoming accessible to even people that don’t know how to code. To be able to look at a process and turn that process into an AI enabled one where humans do less than 20% of the work, I think that’s a huge opportunity for young people because this type of skill is in demand everywhere around the world and in almost every company.
And then for the remaining part, the work that we don’t automate and don’t want to automate is everything that is interpersonal and creative. And I think it’s the sort of core, core of the human existence is to use our creativity and our social skills to advance a mission. And I hope that we will remove everything that.
It’s considered a follow up that needs to be done, or an administrative scheduling task or the management of your taxes is not the reason why we’re on this earth. And I hope that that’s something that will offload to AI very soon.
Brian Thomas: Thank you so much. I appreciate that. Just to highlight a couple things, Alberto AI may be unrecognizable in the next five years.
We know that it is leapfrogging, but we hope. Society, humanity is better because of it. And we, you also mentioned your hope is your platform. B seven is, will help be there to help remove some of that bureaucracy. And I did highlight something that I thought was important is you see an opportunity in the younger generation to actually leverage AI to maybe help tackle a new process or improve a process.
I thought that was really insightful, so I appreciate that. And Alberto, it was such a pleasure having you on today, and I look forward to speaking with you real soon.
Alberto Rizzoli: Thank you Brian. Great to be here. And for anyone that is young and wants to automate a process come talk to us at the V7labs.com, V for Victoria. Have a good day.
Brian Thomas: Bye for now.
Alberto Rizzoli Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
