AI that changes how the company operates — with evidence, authority and control.
I design AI around real workflows, measurable outcomes and the governance required to trust it in a serious company.
Why AI pilots fail
Most companies don’t have an AI problem. They have an operating-model problem with AI sprinkled on top.
Unchanged workflows
The tool is new; the way work flows, decisions are made and hand-offs happen is exactly as before. Nothing measurable can change.
Unclear ownership
Nobody owns the outcome of the AI-assisted process — so nobody fixes it when it drifts, and nobody defends it when it works.
Poor data, no adoption
The system is fed what’s convenient, not what’s true, and the people who should use it were never part of designing it.
No verification
Confident output is accepted as correct output. Without independent checking and an audit trail, trust collapses at the first visible error.
My principle: Redesign the work before automating it.
Five use-case families that survive contact with reality
Every use case is specified the same way: what goes in, what the system does, where the human decides, and what is measured. No “AI transformation” without an example.
1 · Management knowledge & decision support
2 · Quality evidence, CAPA & audit readiness
3 · Workflow coordination & reporting
4 · Operational monitoring & exception handling
5 · Controlled agentic execution
The controls that make AI defensible
The same discipline a quality system demands — because an AI system without controls is an audit finding waiting to happen.
Human authority
AI proposes; accountable people decide. Anything consequential carries a human GO.
Least privilege
Every component gets the minimum access it needs — and nothing more.
Separation of duties
The agent that executes is never the agent that verifies. Independent checking is structural.
Evidence on every claim
Answers carry sources. Unsupported claims are visibly missing their citation.
Permanent audit trail
Proposals, decisions and actions are journaled — reviewable by an auditor, or by you.
Kill switch
Everything can be stopped at once, cleanly. Control you never need is still control you must have.
Built in production, on my own company
These are not concepts. They run real workflows every day and are demonstrable live.
An autonomous AI operating company
Specialist agents propose, execute and verify work under human authority, with separation of duties and a permanent journal.
Private company intelligence
A private model and retrieval system that answers from the company’s own record, cites its sources and refuses to invent what it cannot prove.
Decisions checked across models
Multiple AI models examine the same question and synthesize a cross-checked answer instead of trusting one confident response.
From assessment to production
Find the workflow
One high-value workflow where evidence, speed or coordination is the constraint — chosen for business value, not novelty.
Redesign it
Ownership, decision points and data fixed first. Automation lands on a workflow worth automating.
Deploy with controls
Production deployment with human authority, verification, audit trail and a defined measurement of value.
Prove & extend
Value verified against baseline. Only then does the next workflow follow — capability transfers to your team as it scales.
Identify your first high-value workflow.
Tell me where evidence, decisions or coordination are slowing the company. I’ll tell you candidly whether AI belongs there — and what I would redesign first.
Identify Your First High-Value Workflow