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Case studies Governance Lessons Watch it work The journey How it's built Live health Contact

Questions we answer

Can we trust AI to act on its own?Governance and guardrailsWho allowed the AI to do that?Identity travels with every requestCan someone talk the AI into something risky?Risk-graded autonomyCan we see who did what, and why?One thread from request to resultWhere are the keys kept?One vault, no shared secretsWhy did the AI bill jump, and who spent it?One counted doorwayIs every task getting the right model?Right model, right taskWhat if our AI vendor goes down or raises its price?No single point of supplyAre we paying for tools that do the same job?One tool per jobDoes the AI forget everything between conversations?Governed shared memoryIs this producing real work, or just answers?The digital factoryWhich work should run itself?Managed, not scriptedCan we get more from the Copilot licences we already pay for?Copilot proposes, the platform verifiesWill people actually use it?Meet people where they workHow much time do people lose sorting inbound information?Intake to insight, untouchedCan the same platform run a real business?One governed foundation for every productWhat happens when it breaks at night?Detect, fix, escalateWhere is the list of what is open, and who owns it?One list, closed with evidenceCould we recover if we lost everything?Proven by restoringCan you prove it to an auditor?Challenge before acceptanceDoes it get better over time, or just older?Every lesson becomes a ruleWill this still work after the next upgrade?Clean Core for AIDo our documents match what is actually running?Documentation as a by-productCan we trust AI to act on its own?Governance and guardrailsWho allowed the AI to do that?Identity travels with every requestCan someone talk the AI into something risky?Risk-graded autonomyCan we see who did what, and why?One thread from request to resultWhere are the keys kept?One vault, no shared secretsWhy did the AI bill jump, and who spent it?One counted doorwayIs every task getting the right model?Right model, right taskWhat if our AI vendor goes down or raises its price?No single point of supplyAre we paying for tools that do the same job?One tool per jobDoes the AI forget everything between conversations?Governed shared memoryIs this producing real work, or just answers?The digital factoryWhich work should run itself?Managed, not scriptedCan we get more from the Copilot licences we already pay for?Copilot proposes, the platform verifiesWill people actually use it?Meet people where they workHow much time do people lose sorting inbound information?Intake to insight, untouchedCan the same platform run a real business?One governed foundation for every productWhat happens when it breaks at night?Detect, fix, escalateWhere is the list of what is open, and who owns it?One list, closed with evidenceCould we recover if we lost everything?Proven by restoringCan you prove it to an auditor?Challenge before acceptanceDoes it get better over time, or just older?Every lesson becomes a ruleWill this still work after the next upgrade?Clean Core for AIDo our documents match what is actually running?Documentation as a by-product

Portfolio / Run Like an Enterprise

The business question · Standard first: Clean Core for AI

“Will this still work after the next upgrade?”

The concept

Clean Core for AI

Standard first, custom only by exception, and every change labelled.

How it works: Every need is met in order: buy a proven product, configure it, customize only if needed and build last, with each change labelled.
Why it matters: Upgrades stop being risky, and technical debt stays small enough to manage.
The result: Replacing custom scripts with proven tools removed the most common source of early incidents.

See it workingClean Core for AIAnimation

Every need is met in order: buy a proven product, configure it, customize only if needed and build last, with each change labelled. Animated from the platform's real setup.

The business problem

Most early incidents traced back to home-made scripts.

Custom code written to make a pilot work becomes tomorrow's technical debt. Early in the build, most incidents traced back to home-made scripts.

▶ Watch the answer: Can you prove what your AI did?

Why this concept

Buy, configure, customize, and build last, with every change labelled standard or custom

It is the SAP lesson: fit to standard and keep the core clean, so upgrades do not break you.

Also considered

Keep patching the custom scripts

How it works

Clean Core for AI

Need

A new capability

Buy

A proven product first

Configure

Settings, not code

Customize, then build

Only by exception

Label

Every change marked standard or custom

What we put in place

Researched built-in features, plugins and proven open-source tools before writing any code.
Replaced home-made scripts with proven tools, such as a standard job queue for every server command.
Labelled every change standard or custom, and kept the custom surface small.

The result

Before

Most early incidents traced back to home-made scripts.

After

Replacing custom scripts with proven tools removed the most common source of early incidents.

I bring ERP discipline to AI, where it is badly needed.

In your organization

An AI platform your team can upgrade without fear.

Related case studies

Self-healing operations

“What happens when it breaks at night?”

The conceptDetect, fix, escalate

Read the case study

Incident and task management

“Where is the list of what is open, and who owns it?”

The conceptOne list, closed with evidence

Read the case study

Next case study

Documentation as a by-product

Lessons learned

Contact

Looking for someone to lead AI from pilot to production?

I would be glad to walk you through any part of this live and talk about the role you have in mind.

Email me LinkedIn One-page brief

j.walters@erpaiintegration.com

Go deeper: Lessons · The journey · How it’s built · Live health