AI-augmented software development scan
Is your engineering organisation ready to adopt AI-assisted development safely and at scale? Know within two weeks.
Is your engineering organisation ready to adopt AI-assisted development safely and at scale?
Teams are already using AI tooling, but governance, standards and adoption are inconsistent. Technical debt makes adoption difficult. Leadership expects productivity gains, but the engineering organisation is not yet mature enough to deliver them reliably.
This scan maps your engineering maturity across five dimensions and gives you a concrete path to scalable, responsible AI-augmented delivery.
What we assess
Five dimensions of engineering readiness
Each dimension receives a score, a clear explanation and concrete recommendations for next steps.
- Architecture & platform readiness — application architecture, API maturity, modularity, technical debt, cloud readiness
- Software delivery lifecycle — coding standards, PR workflows, definition of done, release processes, documentation
- Tooling, automation & quality engineering — CI/CD maturity, test automation, quality gates, observability, AI tooling usage
- Organisation & engineering culture — ownership, review culture, leadership alignment, knowledge sharing, change readiness
- Security & governance — AI governance, security standards, compliance, IP protection, responsible AI policies
How we work
| 01 | Intake & questionnaire Digital questionnaire followed by a kick-off session with key stakeholders from IT, engineering and management. |
| 02 | Documentation & tooling review Review of architecture documentation, repository analysis and assessment of existing AI tooling and SDLC governance. |
| 03 | Developer & leadership interviews Our engineers speak with developers and leadership about delivery practices, tooling adoption and engineering culture. |
| 04 | Analysis & scoring We assess all five dimensions, identify risks and bottlenecks, and prioritise the most promising AI opportunities for your delivery organisation. |
| 05 | Presentation & roadmap Findings presented to engineering leadership and MT with a concrete action plan: what to fix first, which quick wins are achievable and what to defer. |
Right for you if
- You want to scale AI-assisted delivery but are unsure if your engineering organisation is ready
- Teams are already using AI tooling, but governance and standards are inconsistent
- You want to improve software delivery speed and quality without increasing technical debt
- Leadership expects measurable productivity improvements from AI initiatives