Governed AI across all your work.
Underneath every A4 application is one governed platform: agents that take on multi-step work, build the tools and views you ask for, search everything you own by meaning, and record every step under the limits you set. Here is how each part works — and why you can run the business on it.
A governed chain of agents: authority narrows as work goes down, and anything consequential stops for a person.
Agents that delegate down — and escalate up.
A single agent rarely does a whole job alone. It breaks the work apart and hands pieces to helper agents below it — then pulls the results back together. The structure is what makes it safe.
A helper can never widen authority. When an agent delegates a piece of work, the helper it launches does strictly less than the agent above it — never more. Authority only narrows as work goes down the chain, so asking the AI can never become a way around your controls.
Anything consequential climbs to a named person. Routine work runs on its own. The moment a decision crosses the line you drew — a payment, an approval, anything high-stakes — it stops and goes to a named human, who approves or rejects. That exchange is on the record.
Every agent runs under a spending limit. Each agent is given a hard spending limit before it starts, and the platform checks the limit before the agent acts. A run that would exceed it is refused, not quietly overrun.
An AI agent can take on an end-to-end accounts-payable review — intake the invoices, validate each one, escalate the calls that need a human, retire when the work is done. Under budget. Every step recorded. The hard part of enterprise AI was never getting an agent to act — it was making sure it can’t reach past its authority, can’t outspend its limit, and can’t make a consequential call without a person. And proving it afterward.
Describe what you need. A4 stands it up.
Most platforms make you choose between off-the-shelf — fast but generic — and a custom build — powerful but slow and expensive. Here you get neither trade-off. Describe a tool, a view, or a dashboard in plain language and the platform builds it on the data you already have, inheriting the same permissions, approval, and audit as everything else.
What it builds is a governed, versioned, reversible artifact — not a one-off script. It runs through review before it goes live, the person who built it can’t wave their own change through, and any version rolls back in a single step.
People and agents stand up new views and tools — no engineering cycle, same governance as everything else.
Every navigation surface a person or agent builds is governed: published org-wide, held as a draft for a separate approver, and previewed live — before and after — before it ever goes live.
The whole build-to-run loop is five moves:
- Connect. Meet your systems where they already live. Keep your system of record where it is; the platform makes it usable by people and agents without a migration, through a catalog of connectors for the everyday business systems you run.
- Land. Bring that data in as governed tables. Incoming data stages first, you preview the result before anything goes live, then promote it — deduplicated, validated, and reversible. If a batch turns out wrong, you un-promote it.
- Build. Compose the operations your assistants reach for and the dashboards and pages your people work in — all described in plain language, all governed by construction, all scoped to the right person, role, or team.
- Act. Let agents drive the same loop people use — under the same permission checks, scoped to their own organization, using connections they can act through but never read. Nothing the agent does sits outside your governance.
- Prove. Everything the loop did — every connect, every change, every action — lands in one place: a single record you can filter, export, and verify on demand.
The result: you extend the product yourself, and what you build is bounded, attributable, and reversible — without having to trust whoever built it. You buy capability on the roles you already run, not another row of seats.
Step one of the loop: a catalog of connectors to the systems you already run — credentials encrypted at rest, every sync run on the record.
Search by meaning — across documents, drawings, and photos at once.
Ask in plain language and the platform finds what you mean, not just what you typed. No keyword guessing, no remembering the exact phrase someone wrote three years ago.
The passage that says it, even with zero matching keywords. Type “corroded valve flange” and the platform returns the paragraphs that mean the same thing — pulled from the right page of the right manual, invoice, email, or report — whether or not they share a single word with your question.
The photos that look like it — and the ones that mean it. Click a photo of a leaking flange and get the other photos of leaking flanges. Type “leaking flange” and see the same set — even for photos with no useful words around them. No one had to tag a thing. Words and images come back in one ranked list.
Every result respects the permission model: a person, or an agent acting for them, only ever sees what they’re already entitled to see. There is no back door around the permissions at search time.
A plain-language question surfaces the right passage, photo, or drawing — with the source right beside the answer.
Every task leaves a record you can read — and an invoice you can read too.
When an agent works, you are not asked to take the result on faith. Every step it took, every change it made, and every dollar it spent is captured as it happens — in plain view, in real time, scoped to your organization alone.
A record of what it did. Per-task execution records show the whole run — what the agent was asked, what it looked up, what it decided, and where it handed work to a helper or back to a person. When several agents work together, you can follow the work as it moved between them.
A record you can prove. Every change lands in one unbroken, verifiable record — what was touched, by whom, and whether it was allowed, including the before-and-after of every write. Alter or delete a single entry and it’s detectable. An auditor can confirm it without taking our word for it.
A cost you can read. Spend is broken out per agent and tracked over the life of a task, so a cost spike lines up with the exact step that caused it. You see what each task cost before the bill arrives — and the limit was already checked before the agent acted.
Nothing to install. Every session walled off to you.
Every agent session runs inside a secure, isolated workspace in your browser. No software to install, no local files to manage, nothing that persists after the session ends unless you choose to keep it. The workspace is scoped to you: files, tools, and connections another person uses in their session are invisible to yours.
Open a task, review the agent’s work, approve or redirect it, and close the tab. The governance keeps running; you don’t have to stay in it to stay in control.
A session in your browser — no install, scoped to you, isolated from every other user's workspace.
Theme the workspace to your brand — app bar, sidebar, and background, in light or dark mode, with a live preview as you adjust.
14,200+ API endpoints. 1,300+ data models. One permission model across all of it.
Every application, every agent, every search result, every audit entry runs through the same governed data layer. There is no separate AI system sitting beside your data: the agents act on the same records your people do, under the same controls, with every action on the same record.
A person’s effective access, resolved per individual across thousands of fine-grained permissions — deny-by-default, broken out by domain, every grant tracing to the role behind it.
Platform capability across one governed data layer — not a single tenant’s usage.
The fastest way to understand it is to watch it run.
Bring an active question — a document hunt, a finance review, a record you can’t reconcile. We’ll open the platform against your data, let an agent do the work in front of you, and show you the answer arrive with the full record behind it.