05 Track record
Client detail is abstracted deliberately — the work was delivered under agreements that do not permit naming. What follows is the shape of each programme and its measured effect; references are available under NDA.
01 Selected outcomes
Each of these was measured before and after. Where we cannot show a baseline, we do not quote a number.
Programme compression
~50%
calendar reduction
Hard regulatory and commercial deadlines on a large cross-system integration. Roughly halved the calendar through tight architectural scoping and AI-accelerated execution — without dropping scope.
AI-native delivery
30–40%
productivity uplift
AI embedded across the lifecycle — story generation, planning, scaffolding, test automation and review. Made the default operating model rather than a tool a few teams picked up.
Quality engineering
80%
manual QA removed
A cross-squad automation programme that removed the bulk of manual regression effort and materially lifted deployment reliability. Quality treated as a product, not a department.
Ground-up platforms
D0→Live
greenfield to production
Net-new production services in Go and Java taken from empty repo to live traffic — CI/CD, quality gates, observability and on-call in place from the first deployment.
Org capability
8×
chapter growth
Teams built from a handful of engineers to full multi-squad chapters, with hiring bars, squad charters and release engineering playbooks that outlasted the people who wrote them.
Delivery infrastructure
10×
faster builds
CI/CD modernisation across a large multi-service estate — pipeline redesign, caching and parallelisation delivering a tenfold build-time reduction, and with it a materially shorter feedback loop for every team on the platform.
02 Lineage
The engineering judgement behind Bluestreak Labs was built over eighteen years inside regulated, latency-critical platforms — where downtime, latency and regulators all had opinions.
Now
A specialist lab applying that lineage to industrial and scientific programmes, with AI-native delivery as the default operating model.
Pillar leadership
Engineering leadership across a multi-squad product pillar in a regulated, latency-sensitive domain — architecture, delivery practice, hiring bar and AI adoption.
Greenfield
Core banking built ground-up — transfers, cards, wallet, bill payments, rewards — and an engineering chapter scaled eightfold around it.
Platform era
Kubernetes-based event-driven platforms in European e-commerce, reactive systems for a large telecom marketplace, and CI/CD modernisation delivering an order-of-magnitude build-time reduction.
03 Domains
Regulated and latency-sensitive by habit. It is why the non-functional baseline is not negotiable.
Sports betting & gaming
Regulated, latency-critical, multi-market
Banking & payments
Core banking built ground-up, high volume
Telecommunications
Reactive platforms at marketplace scale
E-commerce
Event-driven platforms, European scale
Energy services
Field data and industrial instrumentation
Consumer products
Our own apps, six figures of installs
04 On disclosure
A short explanation, because it is a fair question to ask of a technology company.
Most of the work described here was delivered inside organisations under agreements that do not permit us to name them or describe their internals. Rather than stretch those agreements, we abstract: the problem shape, the approach, and the measured effect, with the identifying detail removed.
If you need verification before committing budget, we will arrange a reference conversation under NDA. That is a better basis for trust than a wall of logos, which tells you nothing about who actually did the work.
Reference call
Under NDA we can go considerably deeper — architecture detail, what went wrong, and what we would do differently. Ask for it in the brief.
or write directly — [email protected]