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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 / How it’s built

Architecture

One AI brain, wired into the work.

An assistant in Microsoft Teams that plans, remembers and delegates, backed by a counted model doorway, automation, monitoring and self-healing.

Self-documenting

Drawn from the apps register, rebuilt automatically twice a day.

Rebuilt from the register at the last publish.

Every line in the pictures is checked against the register before the page is published.

The layers

From a sentence in Teams to finished work.

Each layer lists the parts in use today, read live from the register. Version and security detail is left out on purpose.

PeopleThe owner, invited users and website visitors

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Front doorMicrosoft Teams, Microsoft 365 sign-in and single sign-on

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The brainPlans, remembers, governs and delegates

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Models and memoryOne counted doorway, right-sized lanes, independent backups and shared memory

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Executor and specialistCarries out the work; Microsoft 365 work runs through Copilot with verification

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AutomationWorkflows, self-healing, one job queue and the document publisher

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WatchingMonitoring, tracing, uptime checks and one incident system

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FoundationOne server, encrypted off-site backups, certificates and a private network

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ProductsCustomer-facing sites and automations on the same platform

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Design principles

The rules every part follows.

Settle the operating model before the tools

Brain, executor and specialist were defined first; tools were chosen to fit them.

Standard first, custom last

Buy, configure, customize, and build only what is left. Clean Core, applied to AI.

Verify by making it happen

Nothing counts as working until it has been made to happen and watched.

Lead AI agents with a method

Independent review lanes, a sealed first answer and a challenger. No single agent's word is proof.

Governance in proportion to risk

Controls are added when a real failure shows they are needed, so governance stays small and meaningful.

The owner decides, the agents deliver

I own the decisions and trade-offs; the agents do the hands-on work and show their evidence.

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Contact

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