Every engagement is led by Double Six operators — people who have built, rescued and scaled the type of business they're assessing. Situation, problem, outcome — not just slideware that will sit on the shelf.
A well-funded private-equity data platform was building on assumption, not evidence. Product-market fit was asserted rather than proven, the roadmap was driven by a handful of voices — SMEs, not customers.
We defined and evidenced product-market fit from the market in, then rewired prioritisation so every roadmap and investment decision traced to validated demand and commercial pipeline — a defensible articulation of fit, and the foundation to sell the product rather than perpetually rebuild it.
How to enter, and dominate, a crowded, price-driven category years behind well-funded digital natives — with a legacy cost base and a business case resting on customer assumptions in a new category with no established insight.
We tested assumptions to destruction, rebuilt targeting around real customer need and use cases rather than personas, and launched globally on an AI-native operating model built to scale with a lean team — 10% the size of rivals — now winning a growing base with an increasingly best-in-market product, powered by deep product–marketing collaboration.
Every new client and market made a critical platform more expensive to run, not less. Outages, offline deployments and an unmanaged codebase had stalled a flagship international programme indefinitely.
We rebuilt the roadmap around real business capability, installed release governance where there was none, and reset ownership across a complex global organisation. Scale stopped being a cost.
A genuinely novel AI product in a category with no established buying behaviour. Hard to explain, harder to price — and a funding raise depending on it.
We turned the technology into a defined, priced, genuinely sellable product proposition with an investor-legible milestone plan — and designed the product organisation to be built the day funding landed.
In each case, the job was converting an assumption everyone had agreed to stop questioning into something tested — and either proven or replaced.
The product is the visible output; the operating model is what makes value repeatable. We build functions that compound, not ones that simply get busier.
Investor milestones, ROI, board business cases, cost-to-scale. Every decision is argued in revenue, margin or enterprise-value terms.
If you're backing a business — or getting one ready to back — let's talk about what's really driving its value.
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