Enterprise Delivery Consultancy
Programs that ship, platforms that stay secure, teams that get faster. Technical delivery leadership, Agile delivery, cloud security, infrastructure and data, and applied AI under enterprise controls.
Six practices, each with the technical depth to challenge a design and the delivery discipline to land it.
Complex technology programs led end to end: planning, dependencies, risk, release management and executive reporting, with the technical depth to unblock teams.
Scrum, Kanban and scaled frameworks applied with judgement, and the harder part: moving teams and stakeholders from quarterly releases to daily ones.
Multi-cloud security programs that fix what the scanners find, set identity and access standards, and keep them fixed.
Infrastructure that is versioned, reviewed and reproducible, and an operating model that keeps services reliable.
Databases designed, tuned and migrated, external data brought in reliably, and the reporting that sits on top, from a practice that started in database administration.
AI coding agents and evaluation pipelines inside the controls a regulated organization expects: labelled changes, evidence, review by risk and recorded approvals.
Each engagement starts with a short, fixed-price discovery and a written plan. We take a limited number of engagements at a time.
A delivery lead who can read the architecture, run the ceremonies, own the release and report to the steering group, from the first week.
An honest assessment of where a program stands, what is blocking it, and a plan that the teams and the sponsors can both sign.
Teams and stakeholders coached from quarterly or weekly releases to daily ones, with the Jira practice and flow metrics that show it working.
From scanner findings to closed items across many applications, with identity and access standards that stop the findings coming back.
One accountable team from the first question to the last release. Every engagement moves through four stages, and AI is harnessed in each one, in the open and under written rules.
Decide what is worth building, fast. Market and option analysis, build-versus-buy, cost and risk modelling, and working prototypes rather than slide decks.
AI in this stage. Agents research, draft and prototype in days. We check their work, run the cheap experiment before offering an opinion, and record why each decision was made.
Build it properly, with AI writing more of the code. Architecture, build, integration and modernization by senior engineers working with AI coding agents under a written development process.
AI in this stage. Every AI-authored change is labelled, tested and evidenced before it is merged. A new test must fail before it is trusted. A named engineer designs, reviews and approves where risk dictates.
Ship in small, reversible, measured steps. One build promoted through development, lab and production with automated gates at each step. Progressive rollouts, recorded approvals for production, rollback by redeploying from source.
AI in this stage. Agents build, deploy and verify in test environments. A person approves every release.
Run it as if it were our own. Cloud, on-premise and hybrid platforms with observability, alerting and security built in, and the DevOps teams and culture that keep it that way.
AI in this stage. Agents help investigate problems and write up what they found. Every change still goes through source control and review. What runs is measured, and the measurements feed the next evaluation.
Arransystems builds and releases its own software exactly this way. It is the proving ground for every practice on this page.
A founder-led consultancy. You work with the founder directly.
The practice is led by Arransystems' founder, Edward Cook, who has delivered technology for banks, telecoms and retailers in the UK, Asia and North America since 1997, as a technical delivery manager, project manager and engineer, and who has built the firm's own software since 2004.
Working inside large regulated organizations and building a product company from nothing are different disciplines. Having done both is what lets us bring the right amount of enterprise rigour to each client, and no more. LinkedIn profile
The person you meet is the person who does the work
A Canadian corporation serving clients in both countries and remotely
The same methods, scaled down: practical AI adoption
Tell us about the program, the platform or the team, and we will say honestly whether we can help.