We Help Engineering Organisations Become AI Native
We build software factories with your engineers, train them on the new way of working, and modernise the legacy code that holds them back.
Trusted by engineering teams at
How We Work
Vision & Outcome
We align on goals, constraints, and success criteria before any investment
Assessment
We analyse your systems, data, and architecture for AI readiness
Roadmap
A gap analysis and prioritized roadmap, written at our cost
Delivery
We build with your engineers, document everything, and train your people to run it
You see what you get and what it costs before committing further.
We use this framework to pinpoint
Exactly which stage your company is on
Discovery
Getting AI into the company: access, then coordination
Curiosity
No formal adoption; personal accounts
First Licences
A 5-10% pilot group gets access
Wide Individual Adoption
Most use AI; uncoordinated
How do we adopt AI without it going sideways?
Discipline
Making AI work for the team: review, context, security, ownership, ops
Structured Adoption
Standards enforced in tooling + CI
Agentic Team (depth)
Multi-agent, sandboxed; context as code
Operational AI (breadth)
AI across CI/CD, IaC, SRE, product
How do we hold quality as agents write more?
Factory
Making AI work at scale: validation, governance
Lights-on Factory
Agents write the majority of code
Dark Factory
Humans specify; agents implement
How do we validate code safely at machine speed?
Frontier
Undefined; few teams are here, practices still forming
Beyond
Not yet known
What does the next operating model look like?
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Our Core Services
AI Native Transformation
An end to end programme to become AI native across the organisation.
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Results we've delivered
A roadmap to reduce cloud costs and carbon emissions
40%
Potential reduction in carbon emissions
20%
Projected cloud cost savings
100%
Zombie workloads identified
AI training turned 1.5 stagnant years into a 3-day launch
400%
Increase in agentic coding usage
50% → 0%
Developer AI-hesitancy, before and after
+1,030%
Top performer's PR throughput
From fragmented systems to one AI Native data platform
3×
Fewer cloud platforms to manage
60%
Faster data pipeline processing
1 platform
Single source of truth for data & AI
A roadmap to reduce cloud costs and carbon emissions
40%
Potential reduction in carbon emissions
20%
Projected cloud cost savings
100%
Zombie workloads identified
AI training turned 1.5 stagnant years into a 3-day launch
400%
Increase in agentic coding usage
50% → 0%
Developer AI-hesitancy, before and after
+1,030%
Top performer's PR throughput
Want Similar Results?
Let's discuss your engineering challenges and identify the fastest path to production.
Trusted Globally
From European enterprises to organisations across North America, the Middle East, and Asia, our team has built platforms worldwide for two decades.
Success Validated By Clients
re-cinq made me rethink how to use AI in scaled Organisation.
Bjorn Brauel
CTO - Odevo
One person from the team doing the rewrite created a mobile app in 3 days. That's now live in both stores. Previously, no progress had been made for 1.5 years.
Tomasz Maj
Head of Product Ops & Development - Odevo
re:cinq took our fragmented tech stack — three cloud providers, mixed databases, legacy systems — and turned it into a modern platform we can scale.
Markus Brendel
COO - seabo
The re:5 platform helped Ole Larsen, a Danish logistics company, to reduce and report emissions from its 200-truck fleet.
Søren Printz Larsen
CEO - Ole Larsen
re:cinq's KubeCon talk sparked our green tech initiative. Their expertise led to recommendations that could cut our carbon emissions by 40%.
Sietse Bruinsma
Manager Digital Platforms & Cybersecurity - Vandebron
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Common Questions
Most companies stall after the first 10% of engineers adopt AI. Review and CI can't keep up with the volume, the backlog dries up, and adoption stops spreading past the early users. That's one of the stages we work in.