Solutions
Three Problems. One System.
Most growth challenges boil down to one of three things: unclear strategy, a misfiring engine, or a model that doesn’t scale. Rygur’s solution system pinpoints which one you’re facing and what to do next. It starts with diagnostics. It ends with results.
Rygur Focus- Strategy
Rygur Focus helps leadership teams determine what matters most. We assess whether your company strategy is truly coherent, differentiated, context-aware, and actionable; not just aspirational. By examining your strategic choices in light of demonstrated capabilities and market reality, as well as your internal alignment on ambition and priorities, we highlight where trade-offs are needed, where energy should be focused, and what role new technology, such as AI should play in the business. The result is a sharper, shared understanding of the path forward - one grounded in the reality of the business, not generic best practices or unrestrained blue-sky thinking.
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Rygur Engine – Operating Model
Rygur Engine evaluates whether the company’s internal structure, processes, technology, and culture are built to execute at scale. It measures both readiness (roles, decision-making, tooling) and maturity (cross-functional delivery, rhythm, adaptability), identifying friction points that slow momentum or create execution drag. It highlights where internal complexity, leadership bottlenecks, or unclear ownership are hindering throughput and offers clear, actionable ways to strengthen the organisational backbone of the business.
Rygur Edge – Business Model
Rygur Edge assesses whether the company’s commercial model is designed for scalable, sustainable value creation in competitive, dynamic markets. It examines how well the business understands its customers, differentiates its offering, captures value, and grows efficiently across pricing, retention, expansion, and go-to-market. By measuring both readiness (fit to serve and monetise customers) and maturity (efficiency, stickiness, scalability), it helps leadership identify where margin is leaking, growth is stalling, or customer relationships need reinforcement.
Client Stories
We’ve worked with fintechs, banks, and businesses across industries to cut through complexity and build what actually works - in strategy, operations, and growth. These stories draw on work led by Rygur team members over the years, real examples of how focus, better engines, and sharper edges turn talk into traction.
Focus
A global asset manager needed a clear AI strategy and roadmap to turn a broad group vision into practical results within a year. The goal was to define where to play, how to invest, and how to deliver visible progress fast.
What we did
We helped the leadership team translate the group vision into a focused AI plan, by aligning the high-level principles to the divisional strategy. This covered strategic priorities, key use cases, and a governance model for prioritisation and linking investment decisions to measurable outcomes.
Results
The division now has an active AI portfolio across front, middle, and back office. It runs under a clear governance model with ROI tracking and central prioritisation, and several initiatives are already being showcased externally.
Engine
A UK wealthtech start-up was scaling fast but without clarity on what drove performance. Headcount kept rising, but growth in people wasn’t tied to revenue drivers, making it hard to see how the P&L would scale.
What we did
We ran an operational maturity assessment to uncover gaps in process, data, and accountability. Then we built a bottom-up unit economics model to link people cost to revenue activity, surface pricing and cost-to-serve issues, and highlight scalability bottlenecks.
Results
The model now anchors quarterly OKRs and deal design. It helps the team prioritise, align hiring with value creation, and ensure every client and product holds up at the P&L level.
Edge
A UK bank needed to refine its commercial strategy for business deposits as falling interest rates threatened growth and increased funding costs.
What we did
We used behavioural data to segment customers by actual activity and preferences, not demographics. Using historical transactions, we modelled how each segment would respond to rate changes, enabling a sharper pricing and operating model.
Results
The bank now applies this model to manage rate changes with precision. It understands deposit elasticity, has built it into standard operations, and is piloting rate adjustments to optimise its cost of funds.