Built for Real Needs: How Elyos AI built applied AI that works in the real world

Exclusive interview with co‑founder Adrian Johnston

“We didn’t start Elyos to build better software, we started it to take real operational pain off people’s plates. Technology only matters if it shows up and does the job, every single time.”

Elyos AI, founded by Adrian Johnston, Philippa Brown, and Panos Stravopodis, has raised a $13M Series A, marking a significant milestone in its journey to build deeply vertical AI agents for trades and field service businesses. The round follows a period of strong traction and reinforces the company’s conviction that applied AI - when built for the realities of operations - can transform how real-world businesses run.

In this exclusive conversation with Adrian Johnston, co‑founder of Elyos AI, we go beyond the funding announcement to explore the thinking behind the pivot, what customers are really buying, and the mindset required to execute in complex, real-world environments.

When did building Elyos AI feel inevitable?

When we decided to pivot in February last year, it didn’t feel like chasing a trend, it felt like recognising something that had been obvious to us for a long time.

Between Pip (Philippa Brown) running operations at OVO Energy and helping optimise a call centre handling ~19,000 calls per day, Panos building Bulb’s entire call‑centre stack from scratch as CTO, and my own experience running a 30‑person customer support team in a previous business, we’d all lived inside the pain of customer operations.

What made the moment inevitable was that advances in voice and conversational AI finally made it possible to automate the work itself, not just add tooling around it. Once that clicked, it felt irresponsible not to build it. The problem, the experience, and the technology all aligned at exactly the right time.

What are customers really buying when they choose Elyos?

Customers aren’t just buying AI or automation - they’re buying reliability and peace of mind. They want every call answered, every enquiry handled consistently, and their business to feel professional even when they’re stretched thin.

Elyos gives them leverage. It allows small and mid‑sized service businesses to operate with the quality and responsiveness of much larger organisations, without needing to hire or manage big teams.

What mindset matters once execution begins?

The mindset that matters most is being relentlessly grounded in reality. Building real‑world products means accepting messiness, imperfect data, edge cases, and operational constraints - and not using them as excuses.

The founders who win are the ones who stay close to customers, iterate fast, and treat execution as a daily discipline rather than a one‑off phase.

“We didn’t start Elyos to build better software, we started it to take real operational pain off people’s plates. Technology only matters if it shows up and does the job, every single time.”

When something feels inevitable, how do you decide what to move fast on and what to deliberately slow down?

When something feels inevitable, we try to move fast on anything that directly touches customer value, and slow down on everything that creates long‑term constraints.

For us, that meant moving extremely quickly on getting agents live with real customers - handling real calls in messy, real‑world conditions. We were happy to ship imperfectly there because feedback compounds fast.

Where we deliberately slowed down was architecture, reliability, and integration depth. Anything painful to unwind later - data models, call‑handling logic, CRM integrations - we treated as long‑term decisions, even if it delayed short‑term speed. Speed matters, but only if it doesn’t trap you later.

What’s one attractive path Elyos consciously chose not to pursue?

Early on, we consciously chose not to build a generic horizontal voice product. There was a strong pull to create something that worked across many industries or optimised for impressive demos rather than daily operational use.

Instead, we narrowed hard on trades and field services, even though it meant slower initial adoption and more complex edge cases. We believed that if we could handle noisy phone lines, stressed customers, pricing logic, scheduling, and payments in this environment, we would build something genuinely defensible.

Saying no to horizontality early was uncomfortable, but it forced us to build real depth rather than surface‑level capability.

From Series A to what’s next

The Series A is not just validation, it’s fuel for deeper execution. Elyos AI will continue to invest in product depth, reliability, and integrations, while expanding internationally and bringing applied AI to more trade and field service businesses.

For founders building in the real world, Elyos AI’s journey is a reminder that inevitability doesn’t come from hype - it comes from lived experience, focus, and the discipline to execute every single day.