Governed, not static.·Enforceable.·Attestable.·Accountable.
compare Why Machineforce

AI you can actually
let near the business

Most AI tools try to catch a bad answer after the AI has written it. That's a guardrail you can drive straight through. We decide what the AI is allowed to do before it does anything — and that decision isn't made of words it can argue with.

01

Catching mistakes late is not the same as preventing them

Nearly every AI safety feature you've seen works like a spellchecker. The model writes whatever it writes, then something reads it and tries to spot trouble. Every "jailbreak" story you've read is someone getting past that reader.

Ours works more like a job description. Before a unit does anything, it has to fit inside what it was hired to do. The AI can change what it asks for. It can't change what it's allowed to have.

THE USUAL WAY — check it afterwardsAIcheckoutthings slip pastOUR WAY — decide firstAIasksits jobdescriptiongo aheadstoppedevery timeTalk the AI into anythingyou like — it still onlygets what it's allowed.
02

You don't write the rules. Your business already did

There's no settings page where someone types what the AI may do — that's exactly how these things go wrong. Instead we build the boundary out of things your organisation already has:

The job — the role it's standing in for, and who it reports to.The places — which sites, systems and information that role actually touches.Your rules — the limits you already apply to people doing that job, including what needs a signature.

Those three become one boundary. If it wouldn't be a reasonable thing for someone in that seat to do, the unit can't do it either.

WHERE THE BOUNDARY COMES FROMThe jobhow far it can goThe placeswhere it can reachbothmust be trueyour rules — tighten only Locked in and signed. Checked on every single action.
The two halves

People and machines, on the same map

Most companies end up with two separate systems: one deciding what staff can do, another deciding what the software can do. They drift apart, and the gap between them is where the trouble lives. We put both on one map.

VERVpeople

Where a person stands.

You already know your job title. What's harder to see is the shape of your work right now — which calls are actually yours to make today, who you're answerable to on this particular thing, and whose trust you're carrying into it.

Places the people
ONE MAPVpersonMmachinesame rules · same check
MERVmachines

Where a unit stands.

The same idea for something that isn't a person: exactly where it sits, what it may touch, and how far it's currently trusted to go. That position isn't fixed — it can move as a unit builds a track record, and it travels with the unit if it works across more than one part of the business.

Places the machines

The point is that they're the same kind of thing. When an approval comes up, nothing looks in one place for the person's authority and somewhere else for the machine's. It reads both positions off the same map, judges the combination against the same rules, and writes both to the same record. One answer to "who's allowed to do what" — covering everyone, human or not.

The usual approachA list of permissions

Roles and tick-boxes. You either have access or you don't. It can't express "trusted here but not there yet", it doesn't move as someone proves themselves, and it stops at the edge of whichever system it lives in.

arrow_forwardinstead
OursA position

Not on/off — a place on a map, with degrees of trust. It can shift as someone or something earns it. Two of them can be combined when people and units work together. And it carries across the whole business, not just one tool.

MERV places machines. VERV places people. One map, one set of rules, one honest answer to who is allowed to do what.

03

Someone's name is on it

Every unit belongs to a real person. Not a team, not an account — a name. If it can't work out who that is, it won't switch on at all.

And when something's genuinely a judgement call, it doesn't guess and it doesn't quietly proceed. It stops and asks them. The AI never gets the last word on anything the rules don't clearly settle.

the unitwants to actthecheckgoes aheadasks a personstops "Not sure" never means "go ahead". It means someone decides.

How that's different

 ChatGPTClaudeGeminiA MachineForce Unit
What it coversEverythingEverythingEverythingOne clear job
Its limitsWritten instructionsWritten instructionsWritten instructionsBuilt from your business
When it checksAfter it answersAfter it answersAfter it answersBefore it acts
Managing itOne seat at a timeOne seat at a timeOne seat at a timeAcross the whole team
Who's responsibleNobody namedNobody namedNobody namedA person, by name
Paper trailChat historyChat historyChat historySealed and verifiable
Which AITheirs onlyTheirs onlyTheirs onlyWhichever suits the job
Saying noIt decides to declineIt decides to declineIt decides to declineIt isn't the AI's call

To be clear: those are excellent models, and we run all three. The difference isn't the AI — it's everything around it. A unit can be built on any of them.

Don't take our word for it

Talk to one of our units, then try to talk it into something it shouldn't do.

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