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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 · Cost control

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

The concept

One counted doorway

Every AI call passes one gateway that counts, caps and routes it.

How it works: All AI traffic passes one gateway that counts every call by agent and task, caps it, and sends it to flat-fee plans first.
Why it matters: AI spend becomes a predictable line item with an owner, instead of the surprise that gets programs cancelled.
The result: Day-to-day work runs on flat-fee plans, spend is visible by agent, and monthly cost stayed flat while usage grew.

See it workingOne counted doorwayAnimation

All AI traffic passes one gateway that counts every call by agent and task, caps it, and sends it to flat-fee plans first. Animated from the platform's real setup.

The business problem

An AI bill that grows quietly and belongs to no one.

Gartner lists escalating cost among the leading reasons AI projects are abandoned: token bills multiply as pilots scale. Many agents and background jobs call AI models all day. Pay-per-use billing would make the bill unpredictable and impossible to attribute.

▶ Watch the answer: Why does the AI bill keep climbing?

Why this concept

Flat-fee plans behind one counted doorway, with a cap for each agent and a rule that new providers replace, never add

Predictable fees and one counting point turn AI spend from a surprise into a managed line item.

Also considered

Pay-per-use access, reviewed when the invoice arrives

How it works

One counted doorway

Request

From an agent or a scheduled job

One doorway

Counts, caps and routes every call

Flat-fee plan

Takes the everyday work

Spend view

By agent and by task

Result

Predictable AI spend with an owner

What we put in place

Put every model call behind one gateway that counts it by agent and by task.
Chose flat-fee subscriptions over pay-per-use billing, with a spend cap for each agent.
Made it a rule that a new provider is priced as a swap, never an addition.
Learned the lesson early: a pay-per-use balance drained in about a day on large conversations.

The result

Before

An AI bill that grows quietly and belongs to no one.

After

Day-to-day work runs on flat-fee plans, spend is visible by agent, and monthly cost stayed flat while usage grew.

I manage AI cost as a design decision, not as an after-the-fact report.

In your organization

One cost picture for every AI tool, before the bill arrives.

Related case studies

Model routing

“Is every task getting the right model?”

The conceptRight model, right task

Read the case study

Not tied to one provider

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

The conceptNo single point of supply

Read the case study

Next case study

Right model, right task

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