The work between the systems
In every company, someone spends part of their day carrying information between systems that never learned to talk to each other. Why integrations never took that work away, what changed with AI, and what it looks like today.
Every company has one. The person who copies order lines from the ERP into a supplier's portal. Who types invoice totals from a PDF into the accounting system, exports them to Excel for the Monday report, then pastes the report into an email. Nobody designed that job. It grew in the gaps between systems that never learned to talk to each other, and it is some of the most expensive work in the building, because it is done by someone who knows the business.
Why integrations never finished the job
Point-to-point integrations have existed for decades, and they never removed this person, for a simple reason: most of the glue is not data transfer, it is judgment. Is this the same supplier as last month, spelled differently? Which cost center does this line belong to? Is this invoice the one we were waiting for? Code could not answer those, so the integration took the easy half and the person kept the hard half. Every new system added another seam, and another slice of somebody's week.
What changed
An AI that reads a document the way a person does, remembers what it was told, and can act on other systems is exactly the missing piece: it takes the judgment half. We think this is the shift that matters most for the next years of AI in business software. A layer that sits between the systems you already have and does the walking between them, with a human approving what matters, rather than yet another system to migrate to. If you want the full argument, with the history and the failure modes, the long version is here.
What that looks like in Agentique today
Invoices arrive on their own. Connect SPV once (a step we activate together at pilot onboarding) and incoming e-Factura invoices are pulled in automatically, read, filed, and ready to answer questions. The person who used to download and file them gets that hour back. How it works.
Documents become records. Data tables the assistant fills and updates from what it reads: suppliers, contracts, deadlines. The re-keying step disappears, and the table stays queryable in plain language.
Sheets and Drive, both directions. It reads from and writes to the Google Sheets your team already lives in, so a scheduled report can land where people actually look, instead of in one more inbox.
Systems with an API. When one of your systems exposes an API, a scheduled workflow can call it, bring the data back, and cross-check it against your documents. Nothing to buy, just a description of what to fetch and when.
Your own tools. For developers, the same workspace is reachable from any MCP client with one endpoint and an API key. The developer guide.
The AI drafts the email
Recipient, subject, body: everything ready to review
It stops and asks
Nothing is sent yet. You see exactly what would go out
You confirm
One click. Or you cancel, and nothing happened
Only then it goes out
Every send, delete or change in a conversation works this way
And the rule that makes any of this safe to hand over: anything that leaves the workspace or changes a record stops and asks first. Nobody is replaced: the person who did this work is freed from its mechanical half and kept exactly where their judgment matters, at approval.
What we do not have yet
Ready-made connectors for specific ERPs. Today a system needs an API and a workflow that describes the exchange; named one-click connectors are on the roadmap, and we are choosing them by what pilot customers actually run. If you want yours first, say so.
Try it on your own documents
The beta is open, with invite codes and a 30-day trial. Bring a folder of real documents, the messier the better.
Write to us and we will set your team up