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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 / Cost-Smart AI

The business question · Not tied to one provider

“What if our AI vendor goes down or raises its price?”

The concept

No single point of supply

Independent providers stand behind the main model, and any one can be swapped.

How it works: The same gateway can send any request to an independent provider, so when the main model fails another one answers without code changes.
Why it matters: An outage becomes an inconvenience, and vendor negotiations start from strength rather than dependence.
The result: When the main model is forced to fail, a fallback answers.

See it workingNo single point of supplyAnimation

The same gateway can send any request to an independent provider, so when the main model fails another one answers without code changes. Animated from the platform's real setup.

The business problem

When the only provider stops, everything stops.

AI vendors change prices, limits and terms every few months. The platform depends on a main model through a subscription. If that provider stops answering, everything stops.

▶ Watch the answer: What if your AI vendor changes the rules?

Why this concept

Fallbacks across independent providers behind the same doorway, with the switch tested

A fallback on the same account fails at the same moment as the main model. Independence is the whole point.

Also considered

Commit to one vendor and accept the risk
A cheaper model from the same vendor as the fallback

How it works

No single point of supply

Request

Through the same doorway

Main model

Answers first

Automatic switch

When the main model fails or hits a limit

Independent provider

A different company and account

Result

The work carries on

What we put in place

Put every provider behind one doorway, so changing one is a configuration change.
Added an independent backup provider after learning the first fallback shared the main model's account.
Tested the switch by making the main model fail on purpose.

The result

Before

When the only provider stops, everything stops.

After

When the main model is forced to fail, a fallback answers.

I test resilience by breaking things on purpose, not by reading the design.

In your organization

Negotiate with AI vendors from strength, and turn an outage into an inconvenience.

Related case studies

Cost control

“Why did the AI bill jump, and who spent it?”

The conceptOne counted doorway

Read the case study

Model routing

“Is every task getting the right model?”

The conceptRight model, right task

Read the case study

Next case study

One tool per job

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