Case studies
Scaling up a client
Going from a startup to running at scale is one of the hardest changes for a tech disruptor to achieve
CASE STUDY: Scaling up a fintech startup
A fintech startup had secured new investment and faced the challenge every founder dreads: converting that capital into consistent, demonstrable returns at pace. The firm needed to shift rapidly from a founding-team mentality to operating at genuine scale, without losing momentum or investor confidence.
The challenge
The core problem was one of focus. The technology team was capable, but lacked a structured approach to prioritisation, delivery and client experience. Work was being done, but not always the right work, in the right order, to the right standard. Investors needed to see credible evidence that the firm could grow sustainably; not just ship features. And clients, particularly institutional traders, needed to believe the platform was ready to move their business onto.
Methodology
Mark stepped in to bridge the gap between the C-suite, sales, engineering, operations and infrastructure, a role that is often underestimated but is frequently the difference between a scaling firm and a stalling one. He drove a new product roadmap and prioritisation framework that aligned the whole firm around a clear set of outcomes: what problems were being solved, in what order, and why.
Working closely with the engineering team, Mark ensured every delivery was scoped properly, with clear usability goals for traders and a relentless focus on building features compelling enough to pull clients away from incumbent platforms. Support quality was treated as a product feature in its own right: clients would never wait more than an hour for answers to technical queries, whether on desktop or mobile.
Results
The firm doubled revenues within 12 months. It established a strong market reputation in low-latency trading, a highly competitive space where reputation is hard-won, which brought further clients onboard and increased market share. Perhaps most importantly, investor confidence was restored and sustained: the firm had demonstrably made the transition from startup to scale-up, with the operational robustness and delivery track record to prove it.
Turnaround operation
CASE STUDY: Interim CTO for a global oil derivatives market-maker
A major global oil derivatives market-maker needed an experienced technology leader to step in on an interim basis. The firm was facing multiple challenges simultaneously: a new trading platform that was a PoC, a team that needed rebuilding, a legacy pricing infrastructure creating operational risk, and a cybersecurity posture that needed beefing up. They needed a CTO who could take ownership across all of it and deliver at pace.
The challenge
The firm's existing technology was limiting their ability to compete. Traders were pricing products through a slow, operationally risky process that affected the quality and speed of prices reaching clients. The digital trading platform needed a full overhaul to meet the expectations of institutional clients. Infrastructure security and network performance were both areas of concern. And critically, they needed to hire and build a high-performing engineering team capable of sustaining delivery well beyond the interim engagement.
Methodology
Mark took on full CTO accountability from day one. He led a transformation of the pricing infrastructure, reducing operational risk significantly and improving the latency at which prices reached clients via APIs and HTML5 UIs, including building Rust-based server-side components for the most performance-critical elements.
In parallel, Mark built out the engineering team, hiring people who both raised the technical bar and integrated well with the existing culture, creating a cohesive, high-performing environment focused on delivery and innovation. Releases moved to multiple times per week, establishing a rhythm of continuous delivery.
Mark also drove a comprehensive improvement to the firm's cybersecurity posture and network and cloud infrastructure, improving both security and performance in a domain where data integrity and uptime are non-negotiable.
Throughout the engagement, AI tools were introduced thoughtfully and governed carefully, ensuring productivity gains without introducing new risks.
Results
The firm emerged from the engagement
with a modern digital trading platform, a rebuilt and highly capable engineering team, and significantly improved infrastructure across security, performance and reliability. The pricing transformation reduced operational risk materially and improved the speed and quality of prices reaching clients. The culture of delivery Mark established continued to deliver results long after the interim period ended; a mark of a truly hands-on, not just advisory, engagement.
Florida Fintech AI advisory
CASE STUDY: Helping a Florida Fintech manage AI adoption risks
A US-based fintech in Florida engaged Agile Mind to help them navigate the growing risks emerging from their engineering team's adoption of AI tools. Senior executives were concerned, but weren't sure exactly what questions to ask, let alone how to address them.
The challenge
The firm's developers had begun using AI coding assistants and generative AI tools in their day-to-day work. Leadership lacked visibility into which tools were being used, on what data, or whether proprietary data could be leaking to external AI providers. At the same time, they recognised that blocking AI use entirely would put them at a competitive disadvantage. They needed a framework, not a ban.
Our approach
We started with a structured AI risk assessment across the engineering and data teams, mapping which tools were in use, what data they were being used on, and where the exposure lay. We identified several areas of concern, including developers using public AI tools on internal codebases without understanding the data retention policies of those tools, and a lack of any policy governing what could and could not be fed into AI systems.
We then worked with the leadership team to develop a practical AI usage policy; one that enabled productive use of AI while establishing clear guardrails around sensitive data and IP. We advised on tooling options that provided a more hermetically sealed environment for AI workloads, and helped the team understand how to apply the same governance principles to AI that they already applied to other technology.
The outcome
The firm moved from a position of unmanaged AI exposure to one of informed, governed adoption. Executives gained the confidence to have an informed conversation about AI at board level, and the engineering team had clear guidance on what responsible AI use looked like in practice.
Our Clients
We work with a range of fintech businesses, from startups to established companies. Our clients appreciate our expertise in technology leadership, strategy and architecture, and our commitment to their success. We've helped clients from startups in the FX and equities eTrading space, commodities mid-sized, and large, global banks.