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Controlled AI implementation within operational and technical systems.

I help organizations reduce manual work, lower error rates and build scalable processes. With governance, audit trails and full technical control. From document automation to ERP integration and system architecture.

Is this the right fit?

Operational friction limits scalability

  • Processes rely on email and manual handling
  • Growth increases complexity instead of efficiency
  • Errors surface during escalation
  • There is limited visibility and traceability

You are looking for structural improvement. Not isolated automation.

Analyze my process

Map one operational workflow and identify controlled automation opportunities.

AI must deliver value without reducing control

  • AI experiments already exist
  • Governance is unclear
  • You want no black box decisions
  • Compliance and auditability matter

You want acceleration, but controlled.

Discuss AI implementation

Define a controlled and scalable AI roadmap.

The code works. But no one truly trusts it.

  • The codebase grew fast, often with AI or multiple contributors
  • Logic is scattered across layers
  • Test coverage is insufficient
  • Every change feels risky
  • Refactoring keeps getting postponed

You want control over your system again.

Start codebase analysis

Assess structure, ownership and technical debt.

How I work

1

Analyze the process

Map where time, errors, and ambiguity enter the system.

2

Design for control

Separate interpretation from execution. Add validation and review loops.

3

Implement iteratively

Ship in 2 week intervals with measurable impact, no six-month waterfalls.

4

Operationalize

Observability, runbooks, and handover so it stays reliable after launch.

Writing

Need reliable automation or a system that can evolve again?

If you’re dealing with operational inefficiency, inbox chaos, or a brittle codebase? Let’s get in touch.

Get in touch