Services

AI transformation

For product, support, and engineering

I help introduce AI where it creates real business leverage: in product workflows, support, and internal engineering processes. The goal is not a demo effect but actual ROI and sustainable adoption.

Primary outcome

Less manual work.

Additional outcomes

Faster delivery of product and internal improvements.
A more controlled and practical AI rollout.

When this is especially useful

The company wants to adopt AI but does not know where to start.
There is a risk of drifting into random LLM experiments without business outcomes.
You need to improve support efficiency, engineering workflows, or product operations.
You need a pragmatic rollout with control over cost, risk, and adoption.

What you get

A prioritized list of AI use cases with business relevance.
Architecture and rollout plans for practical implementation.
Workflow acceleration without unnecessary AI hype.

What this usually includes

I identify AI use cases with clear business value.

I design AI rollout across product, support, and engineering workflows.

I reduce the risk of random experiments and unnecessary implementation cost.

I help integrate AI into actual team workflows rather than isolated demos.

You can quickly check which engagement format fits best

Send a short brief of the situation and I’ll tell you whether this calls for a Fractional CTO engagement, an audit, a workshop, or more focused support.

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2026-04-053 min read

Where to start with AI in product and support

Most AI initiatives stall not because of the model, but because they start in the wrong place. The best first step is usually a narrow use case with clear ROI, a clear owner, and an explicit way to measure success.

AI TransformationProduct OperationsSupport

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About me

Michael Ledin

A CTO with 16+ years of experience. I help product companies where they need technical strategy, architecture, team leadership, and practical AI adoption.

Fractional CTO / AI and architecture consultant

Fractional CTO and technical leadership.
AI transformation across product, support, and engineering.
Architecture modernization, reliability, and observability.
Infrastructure cost optimization.