John Corley: ‘Our first attempt to build product was a spectacular failure’

Spanish Point Technologies provides software solutions to medium and large businesses based on emerging Microsoft technologiesJohn Corley is the cofounder and chief executive of Spanish Point Technologies John Corley is the cofounder and chief executive of Spanish Point Technologies, a company that provides software solutions to medium and large businesses based on emerging Microsoft technologies. It helps build enterprise software products and intelligent Microsoft-native platforms that modernise complex organisations at scale. Operating across more than 13 countries, Spanish Point Technologies delivers enterprise platforms, AI-enabled cloud solutions and large-scale software systems for customers across Europe and North AmericaDescribe your business model and what makes your business uniqueToday Spanish Point is a software and services company. We continue to provide digital transformation services based on our partnership with Microsoft, particularly in the area of cloud and AI. Our deep technical expertise of these Microsoft technologies combined with our ability to really understand customer problems and create innovative solutions has been key to our success. This is evidenced in our Matching Engine product, a unique solution for the music industry that is used in more than 13 countries and is on track this year to distribute more than €1.2 billion in royalties to more than half a million creators and rights holders worldwide.READ MOREWhat was your ‘back-to-the-wall’ moment and how did you overcome it?We haven’t really had any serious “back-to-the-wall” moment. However, our first attempt to build product was a spectacular failure. We developed a product called LookupPoint that analysed text in emails, Word documents and so on and surfaced useful, connected information from enterprise systems. The customer feedback was really positive, and when I demoed it to the Microsoft office product team in Seattle, I got a standing ovation. What I didn’t realise at the time is that to market and sell a mass-market product would require a massive amount of investment that we just didn’t have. This was a great learning experience for us and the next product we built, the Matching Engine, was much more vertically focused with a clear route to market and predictable investment profile. What were the best & the worst pieces of advice you received when starting out?To be honest, I don’t remember the bad advice. The very best advice I got early on was to focus on being myself when doing things like presentations or talks rather than trying to emulate anyone else. What are your annual revenues and profits?This year Spanish Point announced the expansion of its UK operations following 31 per cent compound annual revenue growth between the financial year 2023 and the financial year 2025. In 2026, the company is set to report earnings before interest, tax, depreciation and amortisation (Ebitda) of about €4 million, with revenue of more than €26 million. The company has recently secured an eight-figure strategic investment that will fund product expansion for the company and support its international growth. Describe your growth funding pathFor the first 20 years of the company, we were completely self-funded. In June, we secured a big investment from a UK-based private equity firm, Apiary, to help accelerate our growth and fund acquisitions. This marks the next stage of our growth as a company. How much has your company invested in AI and how has it impacted on the performance of the business?Matching Engine’s matching module uses advanced AI to determine if the inbound information being processed in the system matches an existing musical work or product. The new AI module enhances how collective management organisations access, analyse and act on their information. It is designed to enable faster, more accurate royalty processing at a global scale. Matching Engine’s AI module enables rights and repertoire functions to identify and resolve matching and attribution issues in real time, reducing delays and errors in royalty processing. By enabling direct interaction with usage and repertoire data through an AI assistant, users can identify discrepancies faster, ensure accurate attribution and improve transparency across payments. The volume of music data is reaching a point where manual processes simply can’t keep up. This is about giving rights organisations the ability to see what’s happening in their systems instantly, fix issues faster and protect the value of every play. IN THIS SECTION