Flagship engagement · 10 business days

Engineering & AI Transformation Assessment.

A focused, evidence-led review for founders and technology leaders who need a clear view of their engineering reality—and a practical plan for what to do next.

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The problem this solves

When the next technical investment is unclear.

Architecture has evolved, delivery has slowed, dependencies have accumulated, or AI opportunities are being discussed without a grounded view of feasibility and risk. Before committing to a rewrite, platform change or AI build, leadership needs a shared picture of the current system and the highest-value next steps.

This assessment is designed to turn scattered technical signals into decisions the business and engineering team can act on.

Who it is for

Founders, CTOs and engineering leaders.

B2B software and fintech teams
Growing engineering organisations
Teams facing complexity, reliability or delivery constraints
Leaders evaluating modernisation or applied AI investments

Scope

What gets examined.

The scope is tailored to the systems and decisions that matter. It is not a compliance certification, penetration test or exhaustive line-by-line code audit.

Architecture & system boundariesCore components, interfaces, data flows, dependencies, deployment topology and key design constraints.

Technical debt & delivery frictionStructural risks, coupling, bottlenecks, operational pain points and constraints affecting change.

AI opportunity & readinessCandidate workflows, feasibility, data/system dependencies, risk, controls and where conventional automation is better.

Deliverables

A decision-ready output.

You receive a concise assessment grounded in the evidence made available during the engagement, with assumptions and unresolved questions clearly identified.

01 / Current state

Architecture overview and system/dependency map.

02 / Risks

Technical debt, reliability, security-boundary and delivery-risk observations, prioritised by materiality.

03 / Opportunities

AI and automation opportunity assessment, including feasibility, constraints and human-control requirements.

04 / Decisions

Options and trade-offs for the most important engineering decisions.

05 / Action plan

Prioritised 90-day roadmap with sequencing, dependencies and suggested validation steps.

06 / Readout

Leadership readout and discussion to align on findings and next actions.

How the 10 days work

Investigate, validate, prioritise.

Days 1–2 · Align

Kickoff, business context, goals, stakeholder interviews and evidence/access plan.

Days 3–6 · Inspect

Architecture, selected code and documentation review, system walkthroughs and risk investigation.

Days 7–8 · Evaluate

Validate findings, compare options and assess AI/automation opportunities.

Days 9–10 · Recommend

Prioritise roadmap, prepare assessment and present the executive readout.

Engagement boundaries

Independent judgement, practical evidence.

I personally lead the investigation and architecture work. The engagement is scoped around a defined system boundary and agreed access. It does not require you to commit to a follow-on implementation project.

Client code, data and documents are handled according to agreed access and confidentiality requirements. Any use of AI tooling on client material must be agreed in advance, with data handling and approval boundaries made explicit.

What I need from your team

A business and technical point of contact
Access to agreed architecture documents and selected repositories or system walkthroughs
Time with relevant engineering/product stakeholders
Clarity on the decisions the assessment should inform