SERVICES
IS THIS YOU?

Your engineers use AI daily. But the platform is too tightly coupled and untested to absorb the output safely.

Mandated to adopt agentic AI with no clear picture of what your platform needs to become first.

Every change slow, risky, and dependent on a shrinking group who still understand the codebase.

Tried modernisation before and watched it stall, overrun, or create more complexity than it solved.

Engineers spending more time working around the platform than building on it.

You know you need to change. But you can't make the business case linking platform investment to commercial outcomes.
OUR APPROACH
AI-First Software Modernisation is Codurance’s approach to building the foundations that achieve your ambitions for autonomous agents operating safely and effectively across your business.
Leveraging 13+ years of software craftsmanship and AI fluency, we apply our framework incorporating architecture, platform, practices and processes in parallel. Discover how we deliver a platform that is safe to work on, fast to evolve and ready to support agents.
YOUR FOCUS (with our help)
Agents orchestrating decisions, automating processes, creating leverage across the enterprise
Both foundations produce outcomes you can point to. Not cleaner code in isolation: a platform that moves faster, breaks less, and is genuinely ready for the AI capabilities your business is building toward.
FOUNDATION 1
Modular, observable, agent-consumable
A modular architecture and an observable platform that AI tooling and agents can safely operate in.
Clean, well-documented APIs and event streams ready for AI agent consumption from day one
FOUNDATION 1
Modular systems AI can reason about
We decompose monoliths using the Strangler Fig pattern and Domain-Driven Design, producing well-bounded, independently deployable services that humans and agents can both safely change. We redesign around API-first principles and event-driven architecture, exposing clean contracts and real-time event streams that agents can subscribe to and act on.
FOUNDATION 1
Observable, cloud-native, scale-ready
You cannot operate AI agents on systems you cannot observe. We instrument your platforms with structured logging, distributed tracing, and real-time dashboards. The cloud-native infrastructure we build scales for AI workloads without compounding spend.
OpenTelemetry · Distributed tracing · Platform engineering · Cloud-native
FOUNDATION 2
Teams shipping safely with AI in the loop
The second is AI-accelerated engineering: the practices and processes that let your teams build, change, and ship with AI without the platform falling behind. Neither alone gets you there.
FOUNDATION 2
Quality at AI speed
Low test coverage is the single most common blocker to safe modernisation. And to safe AI adoption. We rapidly improve coverage using characterisation testing, mutation testing, and TDD coaching. The result is a safety net that makes every change, by humans or agents, faster and less risky.
TDD · Characterisation testing · Mutation testing · Clean code
FOUNDATION 2
Delivery cadence built for change
Modernisation only sticks when your teams own it. Our craftspeople embed in your engineering teams, improving CI/CD, release cadence, and the delivery discipline that lets AI-accelerated change reach production. The skills and practices stay when we leave.
CI/CD · Embedded coaching · Knowledge transfer · Delivery discipline
VISION
We start with your business model, your AI ambitions, and your constraints. From there we design a pragmatic, sequenced modernisation roadmap that delivers value at every stage without stopping the business. No big bang. No multi-year programmes that go dark.
Current state assessment · Sequenced roadmap · Business case
WHAT YOU GET
Both foundations produce outcomes you can point to. Not cleaner code in isolation: a platform that moves faster, breaks less, and is genuinely ready for the AI capabilities your business is building toward.
FOUNDATION 1
AI-ready system
A modular, observable platform. Teams can change it confidently. AI tooling can work within it safely.
Clean, well-documented APIs and event streams ready for AI agent consumption from day one
FOUNDATION 2
AI-accelerated engineering

Illustrative example, your engagement will be scoped specifically to your platform, codebase and business objectives
CLIENT STORIES
Outcomes from real engagements. Each one a proof point for the approach we’d bring to yours.
A PE portfolio company’s platform failed on every second customer. Codurance rebuilt the foundations in-team, incrementally, without a rewrite. Within nine months it supported over a thousand.
9 months
No rewrite Exit-ready
Concurrent incidents eliminated through DDD
A financial monolith was averaging ninety concurrent incidents. Domain-Driven decomposition into bounded contexts brought that to zero. A system humans and agents can both safely change.
12 months
DDD Bounded contexts
Sixty percent faster to production
An embedded SaaS provider couldn’t absorb AI-accelerated output. Codurance embedded TDD, rebuilt the test pyramid, and modernised the pipeline. Time to production fell by 60%
6 months
TDD CI/CD
David Green
Chief Technology Officer at IWSR
Neil Robbins
Chief Technology Officer at Alphatax
Sapankumar Parikh
Vice President of Software Development at eClinicalWorks
Ian Kershaw
Chief Technology Officer at Artlogic
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HOW IT WORKS
Step 1 sets the direction. From there, engineering foundations and system modernisation run together, not in sequence. Each shapes the other. The whole programme stays anchored to what Agentic readiness actually requires, and we revisit that direction after every delivered increment.
We work with you to understand where your system stands today and what is genuinely blocking change. The output is a clear, prioritised roadmap built around your business goals, not a catalogue of technical debt. We revisit it after each increment, because the right next step changes as the system does.
Good foundations are not a prerequisite phase you complete before starting. We build exactly what the next increment of system change requires: test coverage, observability, CI/CD discipline. Each improvement makes the next structural change faster and less risky. No more foundational work than the increment demands.
Agentic readiness is not a future phase. It sets the target for system modernisation from day one, grounded in the AI-native workflows your business actually wants to run. We introduce agent integration patterns, MCP servers, and event-driven contracts as the system becomes ready. When agents run in practice, what they need next feeds straight back into the programme.
GETTING STARTED
Most organisations know they need to modernise. Fewer know which problems to tackle first, or how to connect platform investment to the AI outcomes the business is asking for.
Start with our AI and Engineering Assessment. A two-week, evidence-based review of your SDLC maturity and codebase readiness. You get a scored gap analysis and a prioritised roadmap before any modernisation work begins.
TYPICAL NEXT ENGAGEMENTS
A two-week assessment of your SDLC maturity and codebase AI readiness. You get a scored gap analysis and prioritised modernisation roadmap before you commit to a programme.
Codurance craftspeople embedded in your teams to accelerate agentic AI adoption across the SDLC, stage by stage, with the engineering discipline to keep it safe.
Once the platform foundations are in place, we design, build, and deploy your first AI agents. From scoped PoC to production, with governance built in from the start.
It's Codurance's approach to getting your platform ready for AI agents. We modernise your architecture, platform, practices and processes in parallel, so agents can run safely and at scale without the platform becoming a liability.
Traditional modernisation often treats cleaner code as the goal. We anchor everything to what agentic readiness actually requires and revisit that direction after every delivered increment. The result is a platform that moves faster, breaks less and is genuinely ready for the AI capabilities your business is building toward.
The first is an AI-ready system, meaning a modular, observable platform with clean APIs and event streams that agents can consume. The second is AI-accelerated engineering, meaning teams with the test coverage, practices and processes to ship safely with AI in the loop. Most organisations haven't built either yet, and we build both
No. We decompose the monolith incrementally and build exactly what the next increment of change requires. For one PE-backed SaaS client, we rebuilt the foundations without a rewrite and took the platform from failing on every second customer to supporting over 1,000 within nine months.
Every engagement is scoped to your platform, codebase and business objectives. Recent client programmes have delivered measurable results in six to twelve months, with progress visible after every increment rather than at the end.
No. Our craftspeople work inside your teams, not alongside them. Part of the work is building the skills and practices your engineers need to sustain modernisation on their own once we step back.