ProLearn — Learning Platform
From internal training tool to white label product: designing a learning platform built to scale across organisations
Redesigning a critical financial system for tens of thousands of pension scheme members
The Problem
Professional development inside most organisations is a mess of disconnected systems — mandatory compliance modules in one place, optional courses somewhere else, manager-led programmes nowhere near either. Employees don't know what's available, can't track their own progress, and have little incentive to engage beyond the minimum required.
ProLearn started as a brief to fix this for a single company. It became something more ambitious: a white label learning platform that could be deployed across multiple clients and industries, each with their own content, branding, and workforce needs — without the product fragmenting into a different thing for every customer.
My Role
I came onto this project as Product Design Director, with overall responsibility for the design direction, quality of output, and strategic alignment of the work. Rather than being hands-on in the day-to-day production, my role was to set the vision, hold the standard, and make sure the team — three experience designers, a product manager, and two developers — were producing work that met both the brief and the bar expected at this level of engagement.
In practice this meant owning the visual design direction from the outset, running stakeholder sessions to align on goals and priorities, and making the calls that kept the project on course when the product direction shifted from a single internal deployment to a white label platform. That pivot didn't just change the technical requirements — it changed what success looked like entirely, and steering the team through that transition without losing momentum or quality was as much a leadership challenge as a design one.
The Core Challenge
The hardest design problem on this project had nothing to do with features. It was about learning behaviour itself.
Our research consistently surfaced two distinct types of learner: those who wanted quick, digestible content they could fit into a spare ten minutes, and those pursuing structured, in-depth programmes over weeks or months. These aren't just different preferences — they require fundamentally different information architectures, pacing models, and motivational mechanics.
Designing one product that served both groups equally well, without creating a bloated or confusing experience for either, was the central tension of the entire project. We had to resist the instinct to simply build more — more features, more modes, more settings — and instead find the underlying structure that made both learning styles feel at home in the same product.
Key Decisions
Restructuring the product around learning intent, not content type. Early concepts organised the platform by format — courses here, microlearning there. User testing quickly showed this created friction: people didn't think in terms of format, they thought in terms of what they wanted to achieve. We restructured the entire architecture around goals and career context, letting the platform surface the right format for the right moment rather than asking users to choose upfront.
Designing for the pivot to white label from the inside out. When the product direction shifted to white label, the temptation was to retrofit customisation onto an existing design. Instead, we rebuilt the design system with multi-tenancy as a first principle — visual tokens, content slots, and configurable components that could carry any client's brand without requiring bespoke design work each time. This decision added time in the short term but made every subsequent deployment significantly faster.
Using AI personalisation as a progressive enhancement, not a foundation. We made a deliberate call not to lead with AI-driven recommendations until we had enough user behaviour data to make them meaningful. The onboarding flow collected intent and skill level, then used a rules-based approach initially, with AI personalisation layering in as users built a history on the platform. This avoided the hollow "personalisation" experience common to many learning tools at launch.
Outcome
Tested with a sample group of 25 users, the redesigned platform delivered a 20% improvement in task completion speed, with users describing the learning experience as noticeably smoother and more intuitive than previous tools. Engagement and course completion rates improved, and the white label architecture successfully enabled deployment beyond the original client — validating the strategic pivot the product was built around.