Every figure on this page comes from a value model agreed before the work started, measured against a baseline someone in finance verified. Where a holdout group was possible, the improvement is incremental rather than observed. Nothing here is a projection.

Cumulative client value across the portfolio
Average operational efficiency gain
Each with a signed value model
Revenue created and cost removed
Shipped, adopted and measured
Engineers, scientists, designers, analysts
Delivery and client presence
Cloud, AI, data and implementation
Continuing after project one
Any firm can publish percentages. The question worth asking is what the percentage is measured against, who agreed the baseline, and whether the improvement would have happened anyway. Most impact pages cannot answer those three questions, which is why most impact pages should be ignored.
Ours can. Each number below traces to a named metric in a value model, a baseline verified with the client's finance function before work began, and monthly reporting afterwards. Where we could hold back a control group, the figure is incremental — the improvement that did not happen to the group we left alone.
We also keep the failures. Two engagements in our history did not reach their target, and in both cases a portion of our fee was forfeited under the outcome agreement. That is what makes the rest of the page worth reading.
We had bought software before. This was the first time we bought an outcome and actually received it.
The largest single value line in most of our engagements, and the one clients consistently underestimate before we measure it.
Qualified applicant conversion, lending platform
Lead generation, property operations client
Enquiries saved from unanswered calls
Stalled deals recovered by follow-up agents
Next-best-action ranking in financial services
Field team capacity from intelligent dispatch

Recurring savings are worth more than one-off gains, so we prioritise structural cost removal over efficiency drives that decay.
Cost per customer interaction, voice AI
Median saving after architecture review
Document-heavy intake and review work
Manual report preparation hours removed
After re-engineering inherited data jobs
Discounting stopped for customers who stay
The hardest lever to measure and frequently the most valuable — waste, downtime, attrition, safety and regulatory exposure.
Waste reduction from inline vision inspection
Attrition reduction from decision policy
Mean time to recovery under our SRE practice
Availability across platforms we operate
Automated decisions logged and replayable
Client AI incidents escalated to a regulator
In every competitive market we have worked in, responding first has been worth more than responding better.
Turnaround on credit decisions
First response to inbound enquiries
Weekly hours returned to client teams
Month-end financial reporting cycle
Customer onboarding cycle time
Deployment frequency after CI/CD rebuild
The current-state figure is measured and verified with the client's finance or operations function before any work begins. Estimated baselines are marked as estimates and used only where measurement was genuinely impossible.
Wherever statistically viable a control group is excluded from the intervention, so the reported improvement is incremental rather than coincident with market movement or seasonality.
Value is reported every month against the baseline and reviewed formally with the accountable client executive. Figures quoted publicly are those the client has confirmed.
A two-week value assessment identifies which of the four levers applies to you, quantifies the opportunity and commits to a measurable target.