The Governed AI Workforce
Your private, governed self-improving AI Agents that understands how your company works.
Hire agents with identities, jobs, and budgets. Governed policies enforced before every action. Every job ends in a digital receipt.
It works where your team already works
ZeroH ships inside the Microsoft surfaces your team lives in. The job arrives finished, with its receipt.
And it connects to the rest of what you already run, every connection configured, probed and approved before an agent can touch it. See what it connects to →
ZeroH AssistantYour operations assistant: plan work, schedule, sequence projects.Attached the June invoice, due on the 30th…
ZeroH AssistantMaster services agreement, summary
The app your team uses. The consoles you govern with.
Work happens in Teams. The Governance Console shows you the whole workforce. Studio is where you shape it. Console and Studio are real product screens.
Jobs your Sales Agent is hired to do
Each card is a job in the agent’s portfolio — hire the agent, enable the jobs.
Hover a card for the full trace. Every run ends in a signed receipt.
Watch one job run end to end
The same trace the console shows. Pick a scenario; the honest ones are in there too. Hover the run to pause it; any time.
Your agents work with the tools your team already uses.
The Microsoft surfaces, the systems you run your business on, and any MCP server you want reached, each connected as the person asking, and governed before the call rather than reported after it.
22,000+ apps already ship an MCP server. Yours are one governed connection away: ZeroH connects as the person asking, masks before any model, and puts every call on the ledger.
Connected natively today: 7 systems plus the Microsoft estate, 36 governed tools in the box. Not on the list? Ask: we ship new tools every day, and a connector you need is usually days away.
Outlook
Teams
SharePointCalendar
WordPowerPointDynamics 365HubSpotGitHubJiraGoogle DriveWeb searchGhostAny MCP serverYour own APIIt will tell you what it cannot reach.
An agent that quietly guesses around the data it was not given is the dangerous kind. Ours says so, and waits for a person to decide.
- why
- reason over the real values, not print them into the deck
- category
- Monetary amount (AMOUNT) · your DPO granted this one to you
- for how long
A staged illustration, with sample figures. Live on production today: the masked refusal, the DPO-granted category, the session-scoped lift, and the reveal event on the ledger. Planned (arc CONNMASK): the agent proposing the lift just-in-time with this duration ladder, and the active-grant line you can revoke from any surface.
It already knows how your company works.
Not a model trained on your data, a governed RAG your agents read from. It fills itself out of the work your team is already doing, each agent reads the bases it is attached to and nothing else, and a folder of documents becomes cited answers in about the time this takes to read.
A SharePoint folder you already have, policies, contracts, standards, product docs. Nobody converts anything, and nobody uploads a copy somewhere else.
SharePointPoint at the folder, say who can read it, and pick how its documents are cut. One screen, no integration project, no data pipeline to own.
New knowledge baseThe help desk gets the product base, compliance gets the standards, everyone gets the handbook. Each agent then answers from what it is attached to, and from nothing else.
Any agent, or all of themLiverunning on production today
Every month, your agents can do more than last month.
The corrections your team makes are the training. A job the workforce keeps getting right becomes an entry in your company library, and from then on every agent can run it, for a price you can see. Nothing enters the library on its own: the agents propose, a named person ratifies, and the learning stays your IP, on your soil.
Learned from 60 corrections your team made to the drafts it sent back.
Invoice against purchase order against receipt; the exceptions come to a person.
Clause-numbered, so an answer lands on the clause and page, not on the document.
Security, access, and oversight, by construction.
Security & privacy
Host-side masking before any model call. Reversible placeholders, rehydrated only on your servers. The provider never sees a name.
See the masking walk →Access & controls
Delegated access only: an agent reads what the person asking could read. Every grant expires; every consequential action can wait for a human yes.
How access is governed →Monitoring & oversight
An append-only, hash-chained ledger under every turn. Framework readiness, control traces, and proof packs.
See the evidence →Rules & budgets
Your policies, your approval gates and your spend caps are enforced before the model is called, not reported after. An undeclared field is masked, never guessed.
See the control plane →Every job ends in a receipt.
One page a human can read. Sealed, signed, and ready for your auditor.
Rehydrated at the gate; the mail left with real names.
A rejected hold NEVER rehydrates.
budget checked before it ran
Your tenant. Your soil. Your rules.
ZeroH deploys from the Microsoft Marketplace onto your own Microsoft tenant. Masking, the signed ledger and rehydration run inside your perimeter. No raw personal data ever crosses to a model provider.
- →Masking gatewayPII becomes tokens like [CLIENT-4f9a21] before any model call.
- →Signed audit ledgerAppend-only, tamper-evident, sealed with your organization’s key.
- →Rehydration serviceReal names restored only after approval, only inside your tenant.
- →Approval gatesOutbound sends wait in Teams for a human yes.