The talk will describe how an AI solution can help B2B and B2C customers to restore visibility and control in the rapidly growing subscription economy. The speech will demonstrate how AI can automatically detect and track recurring payments by analysing receipts files and emails, with user consent, helping to forecasting upcoming renewals, and help to categorise spending across AI and other SaaS services. There will be several tools and techniques discussed include OCR for receipt processing, email parsing, and financial insights predictions. The talk focuses on practical AI applications that help optimise spending before unnecessary costs accumulate.
Founded and actively developed Renewly AI, an AI-driven subscription management project exploring how intelligent systems can proactively optimise recurring spending through OCR, email analysis, and automated financial insight generation. Played a key role in enabling secure medical research by delivering data processing pipelines, notification systems, and standardisation solutions adopted by multiple major UK medical organisations and universities, including collaboration linked to Oxford University initiatives. Led the design and implementation of critical backend and infrastructure components, including CI/CD pipelines that reduced development-stage bugs by 80%, and performance monitoring systems that improved platform efficiency by 12% in production environments. Demonstrated leadership through mentoring and supervising three summer interns, guiding them through real-world software engineering practices such as code reviews, system design, and production-ready development. This mentorship directly contributed to improved team productivity and resulted in one intern being successfully recommended for further industry roles. Authored and co-authored peer-reviewed publications focused on healthcare data systems, phenotyping platforms, and autonomous testing practices, contributing original technical knowledge to the UK health data and software engineering ecosystem.
