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AI Systems Consultant

Helping organisations operationalise AI systems safely, systematically, and at scale -- with governance, architectural enforcement, and engineering workflows that hold.

Founder of Mneme HQ -- open-source AI governance tooling. 15+ years with FTSE 100 and S&P 500.

Problem

AI output is scaling. Governance is not.

Most organisations have adopted AI coding tools. Very few have adapted their engineering workflows to account for them. The result: AI-generated code accumulates architectural drift, inconsistent patterns, and governance debt that compounds with every session -- because no session starts with memory of the last.

  • AI output scaling faster than review capacity
  • Inconsistent agent behaviour across sessions and developers
  • No enforcement layer between generation and production
  • Architectural drift that compounds silently
  • Fragmented tooling with no coherent governance model

Services

What I help with

AI Engineering Workflow Design

Design and implement AI-assisted development workflows that are repeatable, governed, and team-scalable. Includes coding agent configuration, context management, and session discipline.

AI Governance Strategy

Build the governance layer your AI tooling currently lacks. Decision records, enforcement policies, architectural constraints, and audit trails that survive team growth.

Coding Agent Implementation

Implement and configure coding agents (Claude Code, Cursor, Copilot) with the guardrails and context architecture needed for production-grade use. Not prompt templates -- systems.

AI Architecture Reviews

Independent review of how AI tooling is integrated into your engineering workflow. Identifies drift, gaps, and systemic risks before they compound.

AI SDLC Operationalisation

Extend your existing SDLC to include AI-specific phases: generation governance, constraint enforcement, review calibration, and evaluation frameworks.

Governance Assessment

Structured assessment of your current AI tooling stack against a governance and operational maturity model. Produces a prioritised remediation roadmap.

Background

Built from implementation, not theory

I have spent 15 years building measurement and data systems for FTSE 100 and S&P 500 organisations -- BT, Dell, Microsoft, HSBC, Coca-Cola. That background shapes how I approach AI systems: from the infrastructure up, not the interface down.

I founded Mneme HQ -- an open-source architectural governance layer for AI-assisted development. The tooling exists because I needed it. The consulting exists because most teams do not yet know they need it.

  • 15+ years enterprise measurement and data infrastructure
  • FTSE 100 and S&P 500 client work
  • Founder of Mneme HQ (open-source AI governance tooling)
  • Technical writing on AI governance (published at theovalmis.com/writing/)
  • Physics degree -- systems thinking applied to engineering problems

Engagement

How to work together

Clients

Who I work with

  • Engineering leaders who need AI governance before it becomes a liability
  • CTOs evaluating AI tooling at scale and needing an independent view
  • Startups building AI-assisted products who need the workflow right from the start
  • Enterprise teams with AI adoption underway but no coherent governance model
  • Investors and advisors who need technical diligence on AI engineering practices

Operationalise AI. Don't just adopt it.

Book a call or send a message. I respond within 24 hours.


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