<h2 id="ember2727" class="ember-view reader-text-block__heading-2">While AI continues to evolve, Eduardo Candela is on a mission to ensure it&rsquo;s used with care, clarity, and confidence.</h2>
As the co-founder and CTO of Maihem, his priority is clear: help enterprises embrace AI with confidence, bridging the gap between cutting-edge technology and real-world deployment.
We sat down with Eduardo&nbsp;to hear more about his mission, the challenges of building trustworthy AI, and how his PhD and industry experience laid the perfect foundation for his entrepreneurial journey.
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<h3 id="ember2731" class="ember-view reader-text-block__heading-3">Let&rsquo;s talk about the origins of Maihem &ndash; how did the idea come about?</h3>
I started my career in the automotive industry, working in Silicon Valley at Tesla, and then later at Bosch Centre of AI. That&rsquo;s where I saw firsthand what we call mission-critical AI: systems being deployed in cars, where safety and performance are essential. It became clear how important it is to not just build powerful AI, but to keep it safe and under control.
Before I worked in Silicon Valley, I did my Masters at MIT, where I also conducted research on using AI in mission-critical decision-making processes. Five years ago, I moved to London to pursue my PhD at Imperial College London to research safety in self-driving cars, specifically how to measure risk and train models to be risk-aware and reliable using reinforcement learning.
Max, my co-founder, took a different path. He was at McKinsey before starting a PhD in Natural Language Processing, where his research focused on how to make generative AI safer &ndash; specifically, how to detect and prevent the spread of conspiracy theories.
We met while still in our PhDs and we immediately connected over a shared passion and a shared question: how do we close the gap between AI research, and real and responsible deployment? Maihem became our answer. It&rsquo;s a way to take everything we learned in research and apply it to help companies deploy AI with confidence.
<h3 id="ember2737" class="ember-view reader-text-block__heading-3">How do you think your background in academia has shaped your startup journey?</h3>
When I left my job in Silicon Valley to pursue a PhD, people thought I was crazy&hellip; walking away from the money and the title. But I knew I wanted to live in the future, to go deep on the questions I cared about. A PhD gave me that.
It&rsquo;s still not common for people in academia to start startups. But for me, it makes perfect sense. You're using science to test ideas, you&rsquo;re running experiments, you&rsquo;re validating things, failing, refining, and spending years going very deep to solve a very specific problem that nobody has solved before. That mindset is exactly what you need to build something from scratch.
Both my co-founder and I completed PhDs, and we&rsquo;ve found that background to be incredibly valuable. It&rsquo;s a huge investment of time and energy, so you have to be really clear about what you want to get out of it. But if you are, it&rsquo;s absolutely worth it.
So while it doesn&rsquo;t have to be a PhD, I really encourage anyone who&rsquo;s passionate about answering hard questions and uncovering truth to consider startups.
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<h3 id="ember2743" class="ember-view reader-text-block__heading-3">There's a lot of uncertainty around AI within the wider population. From your perspective, what are some of the most common misconceptions out there?</h3>
We see it across the board &ndash; people are very aware of AI&rsquo;s power, but there&rsquo;s still a lot of skepticism around it. One of the key things many people don&rsquo;t realise is that these new models are probabilistic. You can give them the same input twice and get two completely different outputs.
That unpredictability can be hard to wrap your head around when you&rsquo;re expecting consistency. Hallucinations are one of the biggest blockers to adoption right now. When an AI gives users a wrong answer, people often lose trust in the entire system and immediately disengage.
Of course, there&rsquo;s a more technical layer to this too, where models can be trained in the wrong direction. But for most users and businesses, the biggest challenge is just getting these systems to perform as expected.
There&rsquo;s a real gap between what people think AI should be capable of and how these technologies actually work. They&rsquo;re still not perfect. We want people to confidently harness the power of AI, while also being aware of the limitations. Bridging that gap between expectations and reality is key.
<h3 id="ember2749" class="ember-view reader-text-block__heading-3">What&rsquo;s the most exciting technical challenge that your team has solved so far?</h3>
One of the biggest challenges we&rsquo;ve been tackling is how to bring user feedback and preferences directly into how AI systems are built and behave.
Right now, AI gets developed by engineers, it&rsquo;s deployed, and then users interact with something that doesn&rsquo;t always meet their expectations. So we&rsquo;ve been asking: how do we close that loop? How do we make users feel in control, and actually get what they want from these systems?
It&rsquo;s really a human&ndash;AI alignment problem, and solving it is key if we want people to trust and adopt these tools.
<h3 id="ember2753" class="ember-view reader-text-block__heading-3">&lsquo;AI Safety&rsquo; can mean very different things to different people. What does that term mean to you, and what does it look like in practice?</h3>
That&rsquo;s a great question. For me, one of the key realisations &ndash; especially during my PhD research on self-driving cars &ndash; is that safety is about performance under constraints.
When I used to run simulations, the safest car was the one that just parked and never moved. Technically, that&rsquo;s &ldquo;safe&rdquo; but it&rsquo;s also useless. All of us, when we take a plane, when we drive a car, when we go out, we're always accepting some level of risk in order to achieve a goal.
The question then becomes: how do we achieve a goal without crossing certain boundaries? How do we maintain control? That&rsquo;s what AI safety looks like to me. The real challenge comes in defining and measuring those limits, and ensuring users feel they are in control.
<img src="https://cdn.sourceflow.co.uk/__gallery/561c8268-1e75-422b-8392-81f08709d05a" alt="" width="600" height="400">
<h3 id="ember2758" class="ember-view reader-text-block__heading-3">What is the biggest challenge in bringing AI products like yours to market?</h3>
The biggest challenge (and the biggest opportunity) is the gap between the development of cutting-edge AI and real-world adoption.
You look at the headlines and see OpenAI, new models, new agents, new startups. But when you talk to enterprises &ndash; and the everyday users within their companies &ndash; there&rsquo;s often a huge disconnect. Most companies don&rsquo;t have the talent, the understanding, or the confidence to use these tools effectively.
I call this the &ldquo;chasm of adoption&rdquo; and that&rsquo;s where we come in to bridge the gap. It&rsquo;s not just about technology, it&rsquo;s about mindset. A big part of the work is education: helping people understand how these systems work, and how to use them safely and effectively.
<h3 id="ember2763" class="ember-view reader-text-block__heading-3">How do you see your technology evolving over the next few years?</h3>
AI will continue to improve and become embedded in every part of life. Our mission is to make sure that progress benefits everyone by making AI safe and trustworthy.
In the short term, we&rsquo;re seeing a flood of new models, agents, workflows &ndash; both open and closed source. But most of what&rsquo;s out there today is still what we&rsquo;d call level one or two autonomy. These tools are co-pilots. They support humans, augment their work, but don&rsquo;t operate independently.
At some point, there&rsquo;s going to be a shift. We don&rsquo;t know exactly when, but we&rsquo;ll move into true autonomy, where these systems don&rsquo;t just assist &ndash; they act on our behalf.&nbsp; That&rsquo;s the big opportunity for us.
Once agents become autonomous, you need to know: are they safe? Are they in control? Can they interact with each other reliably? We&rsquo;re not there yet, but the foundations are being built now. Our goal is to help organisations prepare &ndash; so when autonomy becomes the norm, they&rsquo;re ready.
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<h3 id="ember2769" class="ember-view reader-text-block__heading-3">When it comes to AI trends, what are you most excited about?</h3>
I did my PhD in reinforcement learning, so I&rsquo;ve been close to it for a while. It&rsquo;s exciting to see it finally gaining more attention; I find it very promising. Everyone&rsquo;s talking about it now because it mirrors how humans learn: through rewards and feedback.
With the rise of new models like DeepSeek and others, reinforcement learning is proving to be a really powerful and accessible way to improve agent behaviour. It&rsquo;s a current trend that&rsquo;ll only grow further.
<h3 id="ember2772" class="ember-view reader-text-block__heading-3">And what do you feel is overhyped?</h3>
We hear a lot of talk of AI being super dangerous or close to taking over the world. But that&rsquo;s just not where we are. Especially with LLMs, people sometimes forget that these are just models trained to predict the next token, the next word.
We&rsquo;re nowhere near Artificial General Intelligence (AGI). These systems are not self-improving, they use huge amounts of energy, and they&rsquo;re still far away from replicating human intelligence in many domains. So while LLMs are powerful tools, we&rsquo;ll likely need different, more powerful architectures to get anywhere close to AGI.
<h3 id="ember2776" class="ember-view reader-text-block__heading-3">Maihem is currently a team of five. How has the talent attraction process been for you as a startup?</h3>
It&rsquo;s really exciting, but challenging. Hiring for a startup is nothing like hiring for a big company. I&rsquo;ve done both, and they&rsquo;re completely different worlds. You talk to people coming out of Big Tech and often, they just don&rsquo;t have the mindset or culture fit for a startup.
What you&rsquo;re really looking for is your own SWAT team: strong generalists who are smart, driven, and deeply passionate about the mission. We&rsquo;ve been really lucky with the team we&rsquo;ve assembled. Most of them have been founders themselves, so they already understand what it takes to build something from scratch.
That founder mindset has made a huge difference. Instead of chasing the obvious CVs, we looked for people who genuinely want to prove themselves and make a difference. That&rsquo;s where we&rsquo;ve found the most success.
<img src="https://cdn.sourceflow.co.uk/__gallery/99c75b27-56cd-4e35-9240-86a784b30068" alt="" width="400" height="400">
<h3 id="ember2781" class="ember-view reader-text-block__heading-3">You&rsquo;re obviously incredibly busy. How do you switch off and relax outside of work?</h3>
For me, work-life balance isn&rsquo;t about separating work from life. Finding passion in what you do makes all the difference.
I&rsquo;ve always loved diving deep into tough problems; staying up late solving something challenging never felt like a chore. I love reading, especially about startups and tech. It&rsquo;s not work for me, it&rsquo;s real curiosity.
I also love music; I play piano and guitar &ndash; it puts my brain in a different mode and often helps me solve problems in unexpected ways. And of course, I try to stay active. I play football every weekend and tennis when I can. That's how I keep my energy up!
<h3 id="ember2785" class="ember-view reader-text-block__heading-3">Finally, if you weren't working on Maihem, what other problems would you be trying to solve with AI?</h3>
My passion and career have always been focused on one thing: how to build systems that make smart, automated decisions. Even before everyone was calling it &ldquo;AI,&rdquo; that&rsquo;s what I was drawn to.
So if I weren&rsquo;t focused on helping companies deploy AI safely and responsibly, I&rsquo;d probably be building something similar myself &ndash; maybe a vertical agent tackling a specific, meaningful and safety-critical use case.
I love the idea of building AI that helps people with their mental health, or invest their savings safely. But right now, my goal is to help all of these organisations first, to maximise my impact in the world.
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<img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="746" height="400">
📥 Eduardo is one of the 54 innovative technical founders recently featured in our 'Faces of AI 2025' report, which is available to <a class="HyRpFmCjAWIuRxNzmfOWKyciaWbRBoTwI " tabindex="0" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" target="_self" data-test-app-aware-link="">download for free now.</a>
At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, <a class="HyRpFmCjAWIuRxNzmfOWKyciaWbRBoTwI " tabindex="0" href="https://www.generativegroup.ai/contact-us/" target="_self" data-test-app-aware-link="">let's talk.</a>
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Eduardo Candela is on a mission to ensure AI is used with care, clarity, and confidence.

Why Trust, Not Tech, Is AI’s Biggest Challenge: Eduardo Candela on Founding Maihem

<h2 dir="ltr">Building a startup is tough, but Roshan Tamil Sellvan is working smarter and harder.</h2>
Alongside his co-founder Alan, he launched AdvisoryAI&nbsp;to transform the world of wealth management. Instead of building another AI chatbot, they developed a system that learns from every interaction, adapts to financial advisors&rsquo; unique styles, and stays in line with tough regulatory standards &ndash; saving hours of manual work.
We spoke with Roshan about the surprising way he found his perfect co-founder, how embracing a &lsquo;lazy&rsquo; mindset became a secret weapon, and what&rsquo;s next for AdvisoryAI.
<hr>
<h2 dir="ltr">What specific problem is your startup solving, and why does it matter now more than ever?</h2>
AI is no longer some futuristic concept. Tools like ChatGPT have made everyone realise that AI can write your emails, summarise your documents, and even help plan your next holiday. So why not bring that same magic into financial advising?
But wealth management is a whole different beast. It's full of strict regulations, complex documentation, and professionals who&rsquo;ve been doing things the same way for decades. Many of them are brilliant at what they do, but not exactly thrilled about learning new tech.
That&rsquo;s where AdvisoryAI comes in. We&rsquo;re not just throwing a chatbot into the mix and calling it innovation. We're building an AI that actually understands the advisor&rsquo;s workflow, captures the nuances of client conversations, and generates fully compliant reports. All without the back-and-forth prompt wrangling.
My co-founder Alan ran a financial advisory firm for years, so he saw the pain points up close. Writing suitability reports, annual reviews, meeting notes... It's all incredibly time-consuming. Sure, AI can do it, but we&rsquo;ve gone a step further. We&rsquo;re training it to do it right.
<img src="https://cdn.sourceflow.co.uk/__gallery/ccf70cd2-1f2d-458f-a9f3-bbb397e36ef9" alt="" width="400" height="400">
<h2 class="ember-view reader-text-block__paragraph">How did you and your co-founder, Alan, meet?&nbsp;</h2>
We met at Entrepreneur First, which is a three-month programme with global cohorts in places like Berlin, London, San Francisco, and Singapore. It brings together technical and non-technical people to build startups. About 200 people join each cohort, and I met Alan in London.
If you&rsquo;ve watched Love Island, it&rsquo;s actually a very similar concept. There are nights on the rooftop where people sit around brainstorming and discussing ideas. In that process, everything happens so fast because you have such limited time. You might start working with someone, and realise it&rsquo;s not the right fit. If it doesn&rsquo;t feel right, you have to move on immediately.
It was quite brutal, to be honest. I was working 16, 17 hours every single day (even on weekends) for three months.
<h2 dir="ltr">So in that process, did you explore a few different ideas? Or did you know this was the one for you?</h2>
Each co-founder brings a distinct area of expertise. My background is in Computer Science (I did my master&rsquo;s in Machine Learning) so I can pretty much build anything in any space. Alan had expertise in financial management and we had both worked with a few different people before we teamed up. We both brought significant entrepreneurial experience to the table. I&rsquo;m a third time founder; I'd exited two startups prior to this. And Alan had sold his financial firm as well.
They say you should invest in the founder rather than the idea, because the idea can always pivot. It involved asking a lot of uncomfortable questions, so you know that you&rsquo;re prepared to tackle anything together. That&rsquo;s what happened, and after three months, Alan was the co-founder I ended up with!
<h2 dir="ltr">Wow, that sounds exciting! Was it a tough application process to get onto the programme?</h2>
Yes, it&rsquo;s pretty tough &ndash; they only accept 3% of applications worldwide. It&rsquo;s an intense process with three rounds of interviews where they assess your ability, mindset, and how quickly you solve problems. If the average person takes three months to solve a problem, how can you solve it faster?
They want you to have a founder mindset coming into the programme. Throughout my life, I always ask, what&rsquo;s the quickest way to do this? because I&rsquo;m a bit lazy. I always want to find the quickest solution, and that mindset really helps.
<img src="https://cdn.sourceflow.co.uk/__gallery/e8f14fb4-f534-49df-b92e-c0ec1692a6de" alt="" width="533" height="400">
<h2 class="ember-view reader-text-block__paragraph">Is there something most people misunderstand about AI?</h2>
One of the biggest problems is fear. We found that older professionals have more barriers than young people. They think: I&rsquo;ve been doing this job for 20 years and AI is going to come in and take over my job.
But AI is not here to replace people; it&rsquo;s here to aid you in doing your job in a more productive way. If you&rsquo;re currently spending eight hours writing a report, AI can generate the bulk of it in five-to-ten minutes, freeing you up to do something else. The real challenge is shifting perspectives away from the fear that AI is taking over the world.
<h2 dir="ltr">What&rsquo;s the most exciting technical challenge that your team has solved so far?</h2>
One of the hardest challenges we&rsquo;ve solved &ndash; something that our competitors still struggle with &ndash; is perfecting the feedback loop while simultaneously reducing hallucinations and maintaining creative capabilities.
Think of it like ChatGPT generating a report. You might have to keep inputting further prompts to get it right. We've built a system that learns from those edits automatically. After editing five or so reports, that sixth report will be exactly what you want it to be, the way you would write it. Striking that balance of personalisation, accuracy, and controlled creativity is one of the hardest things to crack in AI, but we&rsquo;ve made major progress.
<h2 dir="ltr">There&rsquo;s a lot of discussion around AI ethics. How do you ensure that your product is deployed responsibly?</h2>
It&rsquo;s important to set clear ethical boundaries, especially in the finance industry. That&rsquo;s why we&rsquo;ve built safeguards into our model architecture.
For example, we train the AI to filter out inappropriate language and proactively analyse outputs against current FCA regulatory frameworks before deployment. Our reasoning pipeline verification process employs multiple specialised models working to validate accuracy and compliance at each step. So if a report doesn&rsquo;t meet a certain quality threshold, the system prompts a rewrite. These layered measures help to ensure compliance and trust in the technology.
<h2 dir="ltr">How about scalability? What&rsquo;s been the biggest challenge in scaling your product?</h2>
Right now, we&rsquo;ve tapped into the UK financial and wealth management market &ndash; we&rsquo;re generating &pound;100k per month, close to &pound;1.2M ARR. But we know there&rsquo;s room for much more growth.
Interestingly, we started out building an assistant, but we realised we were essentially developing a highly effective report-writing tool. And that&rsquo;s something that can be adapted for different industries. We&rsquo;re currently testing with various law firms, where the response has been really promising.
Initially, we weren&rsquo;t as bold in expanding beyond finance. But that&rsquo;s changing. We&rsquo;re also scaling internationally &ndash; expanding into the US, Australia, and Canada. Of course, each market has its own regulations and nuances, but that&rsquo;s part of the challenge we&rsquo;re tackling as we grow.
<h2 dir="ltr">With that in mind, have you thought about how your technology might evolve over the next 3-5 years?</h2>
We're building technology that will transform how financial advice works for everyday people! Within three years, our system will act like a smart virtual assistant that creates perfect reports after client meetings and also helps advisors with scheduling, follow-ups, and spotting important financial opportunities they might otherwise miss. Think of it as giving each advisor a dedicated support team, without the extra cost.
The real excitement is in how this will make quality financial advice affordable for everyone. Today, getting personalised financial guidance often requires having significant wealth. Our technology will dramatically reduce the time advisors spend on paperwork and administrative tasks, allowing them to help more people at lower costs.
Soon, the same quality of financial planning that currently requires a six-figure portfolio will be available to teachers, nurses, and delivery drivers trying to make smart decisions with their first retirement accounts.
<img src="https://cdn.sourceflow.co.uk/__gallery/33cb6f2e-ca4a-41bf-8396-e4e228ce4e12" alt="" width="400" height="400">
<h2 class="ember-view reader-text-block__paragraph">Do you see it transforming into a self-serve tool that doesn&rsquo;t involve financial advisors?</h2>
Yes and no. Think of it like a gym &ndash; you can use the equipment and train yourself (self-serve), but you also have the option to hire a personal trainer (financial advisor). So, it's a hybrid system, not an either-or choice.
Many clients will gravitate toward self-serve digital tools for basic financial tasks and education, while advisors will likely focus on providing higher-value services like complex planning, behavioural coaching, and relationship management.
<h2 dir="ltr">You&rsquo;ve currently got a team of 13 based in London. How have you found talent attraction?</h2>
One of the biggest challenges in hiring isn&rsquo;t technical skills. Rather, it&rsquo;s a mindset and culture fit. We need people with a startup mentality because we move fast, and some struggle with that pace.
We&rsquo;ve created a handbook for potential new hires to give them a flavour of the startup life. But ultimately, we filter candidates early on. Our job listings are transparent and that helps to refine applications. If someone wants a standard 9-5 with great work-life balance, this isn&rsquo;t the place for them.
The second filter is our coding test. It&rsquo;s tough, but it&rsquo;s not necessarily about whether they complete it. We&rsquo;re assessing how they work under pressure: Are they coachable? Do they ask the right questions? Problem-solving is one thing, but the right attitude is what we&rsquo;re really looking for.
We think the opportunity in this space is huge, but the personality has to be the right fit.
<h2 dir="ltr">That sounds intense! When it comes to AI trends, what excites you, and what do you think is overhyped?</h2>
The idea of AI taking over the world&hellip; it&rsquo;s a bit much. There&rsquo;s a lot of talk about AI replacing software engineers, but did computers replace mathematicians? No. AI was created by humans, and humans will always have the advantage because of our ability to think and reason. You still need the creative brain around the technology to make it happen.
AI should help people. I read that the concept of an eight-hour workday was popularised in the early 1900s &ndash; the Ford Motor Company adopted it because Henry Ford believed it was the right approach. But who says four hours isn&rsquo;t productive? If AI handles the repetitive, mundane tasks, we can focus on deeper thinking.
It also gives people space to be better parents, better people, to be present &ndash; and that&rsquo;s something AI can&rsquo;t do.
<h2 dir="ltr">If you weren&rsquo;t working on this startup, what other problem would you like to solve with AI?</h2>
I don&rsquo;t have just one single idea, I have a list! I&rsquo;m always writing them down. I believe in tech for good: AI should be used for the benefit of people, not just to make money for a small group.
If I weren&rsquo;t doing this, I&rsquo;d love to work on something in FemTech. Workplace harassment, sexual violence &ndash; these are issues disproportionately affecting women. I watched my own mother struggle through a career filled with invisible barriers and blatant discrimination. So I&rsquo;d love to contribute to missions in that space.
<img src="https://cdn.sourceflow.co.uk/__gallery/2ed22d06-7bff-4c07-94af-7e5b3abf94ac" alt="" width="400" height="400">
<h2 class="ember-view reader-text-block__paragraph">That&rsquo;s amazing! Outside of AdvisoryAI, what are you into? How do you unwind?</h2>
On weekends, I love visiting parks. I got into birdwatching when I was very small; nature has always drawn me in. Hiking, camping&hellip; just escaping the noise and busyness of the city.
So most weekends, you&rsquo;ll find me in the park, camera in hand, on the lookout for birds.
<h2 dir="ltr">Finally, is there anything else we haven&rsquo;t covered that you&rsquo;d like to discuss?</h2>
I'm still fairly new to the UK and constantly learning about the culture. One thing that stands out is how vital young people are &ndash; not just as future leaders and workers, but as the next generation of everything.
If we don't invest in them well, guide them, listen to them&hellip; honestly, all this innovation we're pouring ourselves into right now could end up meaning very little.
I don't pretend to have all the answers &ndash; definitely not a parenting expert here! But I firmly believe that the world we're trying to build with technology only matters if we&rsquo;re also nurturing those who will inherit it. They're the ones who'll take what we've started and run with it in directions we can't even imagine yet.
<hr>
<img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="746" height="400">
📥 Roshan is one of the 54 innovative technical founders recently featured in our 'Faces of AI 2025' report, which is available to&nbsp;<a class="HyRpFmCjAWIuRxNzmfOWKyciaWbRBoTwI " tabindex="0" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" target="_self" data-test-app-aware-link="">download for free now.</a>
At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, <a class="HyRpFmCjAWIuRxNzmfOWKyciaWbRBoTwI " tabindex="0" href="https://www.generativegroup.ai/contact-us/" target="_self" data-test-app-aware-link="">let's talk.</a>

Building a startup is tough, but Roshan Tamil Sellvan is working smarter and harder.

Revolutionising Wealth Management: The AdvisoryAI Story with Roshan Tamil Sellvan

<h4 class="article-editor-content__paragraph">Katya Lait and her co-founder Jack officially launched nettle in January &ndash; an idea that first took shape in the summer of 2024. Now, just three months in, they are well on their way to tackling a major inefficiency in the insurance industry.</h4>
Risk engineers were spending 90% of their time buried in analysis and report writing. nettle is flipping that ratio, significantly cutting the time spent on reports and giving risk engineers back the time to do what they do best.
We spoke with Katya to hear how nettle came to life, the challenges they&rsquo;ve solved so far, and what&rsquo;s next on their startup journey.
<hr>
<h2 dir="ltr">Let&rsquo;s talk about nettle! What specific problem are you solving?</h2>
In short, we&rsquo;re making the commercial insurance market more efficient. Everything from an oil rig to a fleet of company cars can be insured but, in order for the policies to be written, these assets need to first be assessed. These assessments are carried out by professionals called risk engineers.
Risk engineers are often highly experienced and have extensive industry knowledge which makes them uniquely qualified to assess these assets. They complete the assessments in person which is perhaps the most interesting part of the job because they get to meet people, take observations, and give them suggestions to improve. Unfortunately, it's also the part of the job that takes up the least time &ndash; and it's something they'd like to go back to doing more.
Most of their time (about 90% of the job) is spent on analysis and report writing. nettle is reducing that 90% down to 10%, making risk assessments more efficient and giving back the time to do more projects and assessments. So we&rsquo;re looking at an 80% reduction in the time spent per project. In effect, that creates four times value per risk engineer in an organisation.
<h2 dir="ltr">How did the idea come about?&nbsp;</h2>
Jack and I started the business together last year; the nettle of today is the combination of work we were both doing in our respective projects. The idea for the underlying technology originated from a research project I was working on at Quantum Black, which involved researching and building their pioneering multi-agent system now referred to as AgentFlow. Our focus was on automating the writing of credit memos for big banks &ndash; a document not too dissimilar to a risk engineering report.
Today's use case and the problem we tackle at nettle came from Jack, who spent six years in McKinsey working across insurance. Throughout that time, this opportunity kept coming up in strategic advisory projects for insurance enterprise clients. They wanted to grow commercial underwriting but the biggest bottleneck was this risk assessment step, which is unavoidable.
That&rsquo;s where the idea for nettle was born, and my technical skill set complemented Jack&rsquo;s vision well. We got to ideating, talking to potential customers, and went from there!
<img src="https://cdn.sourceflow.co.uk/__gallery/568fc785-3a23-4935-a8e5-1efa44819cff" alt="" width="445" height="400">
<h2 class="article-editor-content__paragraph article-editor-content__has-focus">Do you find there to be any common misunderstandings about AI when talking to customers?</h2>
We typically have two kinds of conversations.
The first is always the best. They get excited and start asking us, &ldquo;Can it do this? Can it do that?&rdquo;&nbsp; We&rsquo;ll get a list of 10&ndash;20 things they want nettle to do. It&rsquo;s great and exciting, but building the kind of features they want takes time, and we have to temper expectations a little bit in the short term. We put our users at the heart of every decision, so we prioritise the AI features that create real value and avoid adding unnecessary features just for the &lsquo;wow&rsquo; factor.
The second is more difficult. They may misunderstand what's happening, so they'll think that we&rsquo;re reading all of their data, all of their personal information. They don&rsquo;t trust the system and want us to list every single source we use.
For us, it&rsquo;s a balance. Obviously, we want to create trust within the product, but multi-agent systems are very complicated and dense in their workflows. We pull data from many sources and process them in complex ways, so we have to make tradeoffs between creating trust and not completely overwhelming them with what's going on in the background.
<h2 dir="ltr">What&rsquo;s the most exciting technical challenge that your team has solved so far?</h2>
This is super specific to a current client we're working with, but it's deploying an open-source model and building an entirely secure on-prem solution.&nbsp;
We're working in a country right now that has strict data sovereignty laws, so no customer data can leave the region. This ruled out using OpenAI or other services that would&rsquo;ve made our jobs easier. Instead, we built this multi-agent system using in-house solutions, open source models, and internal GPU and cloud servers. It was definitely intense, but we got there in the end.&nbsp;
<h2 dir="ltr">Wow! How long does it take to do something like that?</h2>
Thankfully, the way we built our agent system means replacing the underlying model is pretty quick. The challenge was working with a model that's not as smart and making it more robust with limited resources. It involved more sophisticated prompting and optimisation of the available context. But honestly, finding a GPU took the most time.
We couldn&rsquo;t rely on AWS, Azure, or Google, so it was all on-prem and fully in-house. But we&rsquo;ve learned a lot about how to build a safe and robust AI platform. When we work with clients in regions with more open data laws, we will be able to leverage the latest AI models while also delivering a highly secure solution.&nbsp;
<h2 dir="ltr">What is the biggest challenge in bringing AI products like yours to market at scale?</h2>
Scalability isn't top of mind yet. We&rsquo;re still in our first year, building bespoke versions of nettle for clients. Year Two is when we&rsquo;ll step back, consider the ecosystem of solutions we&rsquo;ve built, and focus on scalability.&nbsp;
That said, some obvious steps we&rsquo;re taking in the short-term are to distribute requests across our specialised agents, reducing unnecessary calls to APIs and building generic components we know we will reuse across all our clients. As much as we can, we cache everything and have the system learn from itself &ndash; a crucial feature for our mission to close the knowledge gap in risk engineering.
<h2 dir="ltr">That makes sense. What has been the biggest challenge in your startup so far?</h2>
Bringing AI to new markets! Beyond data sovereignty and creative use of open-source solutions as I&rsquo;ve mentioned, the biggest challenge has been translation.&nbsp;
We&rsquo;re working in a country where English isn&rsquo;t spoken, so we have a pretty sophisticated AI system that reasons in English but delivers results to the user in their language. We have a very complex workflow around this, but it's pretty bulletproof at this stage. It also means that we can support this in virtually any country moving forward.
<img src="https://cdn.sourceflow.co.uk/__gallery/711c6398-64c5-42ee-8b9e-b8d07f8cba40" alt="" width="446" height="400">
<h2 class="article-editor-content__paragraph article-editor-content__has-focus">You&rsquo;re only three months in and already doing great things! How do you see your technology evolving over the next few years?</h2>
Right now, we&rsquo;re positioned as an in-house solution for a specific function in insurance companies. For Series A and beyond, we&rsquo;re considering two directions.
One is expanding into risk assessments: becoming not just a tech company, but also a service company. It&rsquo;d involve getting the most advanced hardware to do our assessments and becoming a centre of excellence on risk assessment. The other option is producing software and hardware together, bringing in drones and 3D visualisations that feed directly into our platform.
There's a lot still to be uncovered. When we come into an organisation &ndash; one of the big three insurers, for example &ndash; it's challenging to get them to migrate from their existing solutions. Often, it's not ideal and it'll never be able to support the AI things that we can do. Instead of forcing migration, we could build an AI agent that runs alongside their current system, and controls their machines to fill in reports automatically with their existing software.
<h2 dir="ltr">When it comes to AI trends, what do you find exciting?</h2>
For me, it&rsquo;s all the amazing developer tools that are coming out right now!&nbsp;
I am just so much faster. What we&rsquo;ve achieved in the past three months is fuelled by the amount and quality of the AI tools I have at my disposal. I&rsquo;ve got an AI agent reviewing all my code, catching errors I wouldn&rsquo;t have spotted. It&rsquo;s accelerated everything and made our platform so much more secure.
We're testing everything on the market right now. Anytime I hear about it's a new dev tool, I test it out immediately. It&rsquo;s exciting because the four of us can now do the work of 10 engineers.
<h2>Which are your favourites? Any recommendations?</h2>
Oh yeah! I like Qodo &ndash; that&rsquo;s what I use to review my code. We use Granola for all our meetings: it's so helpful for us when we're doing tech overviews and onboarding people via Zoom. The obvious one is GitHub Co-Pilot&hellip; everyone's using that, it's fantastic. Cursor is also really good.
My all-star favourite &ndash; it's not quite a dev tool, but it's one that I use about 20 times a day &ndash; is Claude. It's my thought partner during the day; I constantly have it open to ask quick questions.
<h2 dir="ltr">And is there anything in the AI world that you think is overhyped?</h2>
Not overhyped per se, but I&rsquo;ve been underwhelmed by some built-in AI features in tools like Word or Notion. They&rsquo;re pushing them a lot, but I still see a bit more room for improvement there.
I&rsquo;m also not sold on AI personal assistants that respond to emails and manage your calendar. I've heard about people who end up having their inbox full of AI talking to each other - it kind of misses the point of an email!
<h2 dir="ltr"><img src="https://cdn.sourceflow.co.uk/__gallery/ba54ef3b-642d-4e8a-b68c-90a3da34c684" alt="" width="401" height="400"></h2>
<h2 dir="ltr">You must be incredibly busy. How do you relax outside of the work you do?</h2>
Not a whole lot these days! I&rsquo;m obviously working a lot, but I recently got an Apple Watch, so I&rsquo;m trying to be more active when I can. The way they&rsquo;ve gamified it helps me to stay motivated.
<h2 dir="ltr">Finally, if you weren't working on Nettle, what other problems would you be trying to solve with AI?</h2>
Well, this is a good opportunity to shout out another startup on the Faces of AI list &ndash; MAIHEM. What they&rsquo;re doing is super exciting.
If I wasn't working on something industry-specific, I would definitely be in the realm of dev tools and AI for tech developers. That&rsquo;s an area that&rsquo;s going to balloon like crazy and I can&rsquo;t wait to see what comes out of the space.
<hr>
<img src="https://cdn.sourceflow.co.uk/__gallery/1993f6aa-ebed-4306-a563-2ddf177443ce" alt="" width="746" height="400">
📥 Katya is one of the 54 innovative technical founders recently featured in our 'Faces of AI 2025' report, which is available to <a class="article-editor-content__link article-editor-content__link" href="https://www.generativegroup.ai/reports/faces-of-ai-2025/?utm_source=linkedin&amp;utm_medium=social" rel="noopener noreferrer">download for free now.</a>
At Generative, we work with AI-driven startups to scale innovation, refine strategy, and accelerate growth. If you're building in AI and looking for the right talent to take your company to the next level, <a class="article-editor-content__link article-editor-content__link" href="https://www.generativegroup.ai/contact-us/" rel="noopener noreferrer">let's talk.</a>

Katya Lait and her co-founder Jack officially launched Nettle in January – an idea that first took shape in the summer of 2024. Now, just three months in, they are well on their way to tackling a major inefficiency in the insurance industry.

Solving Insurance’s Biggest Bottleneck: In Conversation With nettle's Katya Lait

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Specialists In&nbsp; Industry 4.0 Recruitment&nbsp;
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At Generative, we don&rsquo;t just fill roles &ndash; we help businesses build the teams they need to thrive in the era of Industry 4.0. By focusing on Automation, Data, and AI/ML.&nbsp;
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Far beyond just filling open roles &ndash; We leverage or team&rsquo;s in-depth automation and AI expertise to help streamline your hiring process and achieve your goals.&nbsp;
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If you&rsquo;re ready to build an agile &lsquo;Industry 4.0 ready&rsquo; team that understand how AI/ML, data, and automation can propel your business forward, we&rsquo;ve got the connections to secure the right talent.&nbsp;
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<h5 class="Paragraph SCXW148639536 BCX0" lang="EN-GB" xml:lang="EN-GB">The Challenges We Solve For You&nbsp;</h5>
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We address the scarcity of specialised automation talent with our in-depth industry expertise&nbsp;
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We secured 15 engineers across both disciplines, strategically located in the US and EU, and provided end-to-end support with onboarding and logistics. &nbsp;
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<h2 class="Paragraph SCXW235710044 BCX0" lang="EN-GB" xml:lang="EN-GB">Proven Results&nbsp;</h2>
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