Today we're announcing a partnership with Dromologue aimed at what we call the “full-stack AI transformation problem”: the gap between an organisation's ability to ship software safely with AI, and redesign the business operating model and organisation transformation required to fully exploit the value of AI.
Enterprise AI conversations tend to collapse two distinct questions into one: "How do we realise the value of AI in our SDLC?" and "How does our business operating model need to evolve?" These require different skillsets, yet most vendors address only one in isolation, when the real value of AI is only unlocked by tackling both in parallel.
AI is making developers faster at writing code, but is software reaching customers any faster? For most organisations, no. Coding is only one stage of the Route to Live: once code is written, it still has to clear testing, security, governance, compliance, approvals and release management. This is where the time is really lost. We've seen change approvals take up to eight weeks and peer reviews take days; one global financial institution we've worked with was running 95% manual testing, with a three-week regression cycle for every feature. None of that disappears because code gets written faster. AI just makes the bottleneck more visible, pushing more volume through pipelines already struggling to cope. This is the 80% problem: accelerating one part of delivery without fixing what comes after. It's why platform engineering matters: a faster, more consistent, governed Route to Live for everything AI now helps you build.
Even where agents are participating in the wider SDLC,we've found a second gap opens one layer up. 83% of organisations have adopted AI agents; only 16% have redesigned the work around them, according to Deloitte/Salesforce research. Most AI investment goes into the 30% of the problem that is algorithms and technology, while the 70% that determines whether it moves the P&L - people, process and policy - is left unaddressed or handled case by case.
That's where Dromologue comes in. Their answer is guidance on nine critical components of an AI-native operating model - how organisations organise, build and assure – that can be delivered as a set of agent skills that teams use as they build.
Together, we've designed this partnership to close both layers at once: ClearRoute gets agents live in the SDLC to solve the 80% problem, while Dromologue redesigns the operating model (the people, process and policy layer), so the organization is built to capture the value that faster shipping creates.
software that ships faster and more safely, on an operating model redesigned in step with it — so the value AI unlocks in the SDLC doesn't stall the moment it reaches the rest of the business.
"Shipping software safely at pace and redesigning the business around AI are two different problems. This partnership means our clients don't have to solve them with two different vendors, two different timelines, or two different stories for their board."
CEO ClearRoute
“AI-native isn't just technology state, it's an operating model. This partnership means the operating model gets built at the same speed as the software, not bolted on afterward."
ClearRoute is a global AI-native platform engineering consultancy that helps enterprises transform the Route to Live and reliably bring high-impact digital products to market faster, cheaper, and safer. Its AI-native engineers use a proprietary QCE framework and internal agentic AI platform to transform the Route to Live at pace and scale so teams can move faster, innovate better, and compete more.
Dromologue is a software and advisory company offering services and software to enterprises implementing AI. Founded by Justin Arbuckle, former tech exec at GE Capital - global chief architect, Chef Software - GM EMEA, Scotiabank - SVP Platforms, HSBC - CTO Wealth and Personal Banking, and Schroders - Head of Enteprtise Technology.
Dromologue specialises in the business and technology operating model design and organisational transformation required to fully exploit the value of AI.
Today we're announcing a partnership with Dromologue aimed at what we call the “full-stack AI transformation problem”: the gap between an organisation's ability to ship software safely with AI, and redesign the business operating model and organisation transformation required to fully exploit the value of AI.
Enterprise AI conversations tend to collapse two distinct questions into one: "How do we realise the value of AI in our SDLC?" and "How does our business operating model need to evolve?" These require different skillsets, yet most vendors address only one in isolation, when the real value of AI is only unlocked by tackling both in parallel.
AI is making developers faster at writing code, but is software reaching customers any faster? For most organisations, no. Coding is only one stage of the Route to Live: once code is written, it still has to clear testing, security, governance, compliance, approvals and release management. This is where the time is really lost. We've seen change approvals take up to eight weeks and peer reviews take days; one global financial institution we've worked with was running 95% manual testing, with a three-week regression cycle for every feature. None of that disappears because code gets written faster. AI just makes the bottleneck more visible, pushing more volume through pipelines already struggling to cope. This is the 80% problem: accelerating one part of delivery without fixing what comes after. It's why platform engineering matters: a faster, more consistent, governed Route to Live for everything AI now helps you build.
Even where agents are participating in the wider SDLC,we've found a second gap opens one layer up. 83% of organisations have adopted AI agents; only 16% have redesigned the work around them, according to Deloitte/Salesforce research. Most AI investment goes into the 30% of the problem that is algorithms and technology, while the 70% that determines whether it moves the P&L - people, process and policy - is left unaddressed or handled case by case.
That's where Dromologue comes in. Their answer is guidance on nine critical components of an AI-native operating model - how organisations organise, build and assure – that can be delivered as a set of agent skills that teams use as they build.
Together, we've designed this partnership to close both layers at once: ClearRoute gets agents live in the SDLC to solve the 80% problem, while Dromologue redesigns the operating model (the people, process and policy layer), so the organization is built to capture the value that faster shipping creates.
software that ships faster and more safely, on an operating model redesigned in step with it — so the value AI unlocks in the SDLC doesn't stall the moment it reaches the rest of the business.
"Shipping software safely at pace and redesigning the business around AI are two different problems. This partnership means our clients don't have to solve them with two different vendors, two different timelines, or two different stories for their board."
CEO ClearRoute
“AI-native isn't just technology state, it's an operating model. This partnership means the operating model gets built at the same speed as the software, not bolted on afterward."
ClearRoute is a global AI-native platform engineering consultancy that helps enterprises transform the Route to Live and reliably bring high-impact digital products to market faster, cheaper, and safer. Its AI-native engineers use a proprietary QCE framework and internal agentic AI platform to transform the Route to Live at pace and scale so teams can move faster, innovate better, and compete more.
Dromologue is a software and advisory company offering services and software to enterprises implementing AI. Founded by Justin Arbuckle, former tech exec at GE Capital - global chief architect, Chef Software - GM EMEA, Scotiabank - SVP Platforms, HSBC - CTO Wealth and Personal Banking, and Schroders - Head of Enteprtise Technology.
Dromologue specialises in the business and technology operating model design and organisational transformation required to fully exploit the value of AI.