We guide engineering teams through controlled AI adoption.

.consulting helps engineering leaders place AI, set guardrails, and prove speed gains without losing review quality.

Engineering leaders reviewing AI rollout decisions
Co-founder-led workshop discussion
Engineering workflow review in an office
Team reviewing an approved AI workflow
Two engineers reviewing adoption evidence at a laptop
Small team mapping AI workflow decisions

AI is already inside delivery. The operating model often is not.

From AI activity to controlled adoption

Choose the option that matches your current need: control, implementation, or enterprise governance with compliance evidence.

Explore services
Risk, control, and KPIs3 months

AI Control Foundation

For engineering organizations that need to identify valuable AI use cases, reduce internal risk, and create a measurable operating model before scaling usage.

  • Approved AI use cases
  • Governance and review rules
  • KPI baseline and observability plan
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Tools, workflows, and productivity4-5 months

AI Workflow Implementation

For companies ready to implement AI into engineering workflows, developer tooling, and delivery processes without weakening quality or accountability.

  • AI-enhanced engineering workflows
  • Tooling integrated into delivery chains
  • Productivity and quality evidence
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Enterprise controls and compliance6 months+

Enterprise AI Governance & Compliance

For larger or regulated companies that need AI governance across engineering, security, legal, procurement, compliance, and audit requirements.

  • Enterprise AI operating model
  • AI Act and ISO-oriented compliance mapping
  • Audit-ready governance evidence
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How we turn AI use into controlled engineering workflows

01

Diagnose & baseline

We map current AI use, identify valuable workflow candidates, and define the metrics that matter before rollout claims start.

  • Use-case map
  • Risk/value view
  • KPI baseline
02

Define controls

We turn company, security, and regulatory constraints into practical rules engineers and managers can actually use.

  • Guardrails
  • Review rules
  • Control owners
03

Implement workflows

We embed approved AI usage into delivery routines, developer tooling, documentation, testing, and review paths.

  • Workflow playbooks
  • Tooling paths
  • Team enablement
04

Measure & transfer

We track adoption, quality, and delivery signals, then hand over a model leadership can operate after the engagement.

  • KPI reporting
  • Operating cadence
  • Evidence pack

Clear before rollout

ScopeWhich AI use cases are approved
ControlWho owns rules, review, and exceptions
EvidenceWhich metrics prove adoption is working

The people behind the work

Hauke Rux, Founder & Managing Director

Hauke Rux

Founder & Managing Director

Leads scope, governance, and executive alignment for delivery decisions.

Marius Gill, Founder & Managing Director

Marius Gill

Founder & Managing Director

Turns goals into service design, delivery choices, and measurable outcomes.

Bastian Neubecker, AI Implementation Engineer

Bastian Neubecker

AI Implementation Engineer

Connects use cases with developer workflows, code review, and tooling realities.

Marcos Alves Pereira, AI Implementation Engineer

Marcos Alves Pereira

AI Implementation Engineer

Designs secure workflow paths, enablement material, and day-to-day usage guidance.

Nico Cham, AI Implementation Engineer

Nico Cham

AI Implementation Engineer

Builds evidence, documentation, and feedback loops for teams.

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More team members

Additional specialists when your project needs scaling support.

Useful writing for technical leaders

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Scale AI in engineering with control.

We help define the workflows, guardrails, and proof you need.

Get in contact