An order arrives as a PDF. Someone in the back office opens it, looks up the address, matches the item numbers, creates the transaction. Two to five minutes, depending on how many lines are on it. At a hundred orders a day, that is one full position doing nothing else. And it is only one of many back office processes that AI can take over today.

Since Microtech Büro+ ERP gained a GraphQL API, much of this work can be handed to AI. The open question is how. There are three options, and they differ mainly in how much checking sits between the AI and the ERP, and who is responsible for it.

The GraphQL API is the foundation for AI in Microtech Büro+ ERP

Microtech Büro+ ERP can be read and written from the outside through its GraphQL API, and that is the precondition for any kind of AI automation. Addresses, articles, transactions and open items can be queried, created, changed and posted.

Add the Model Context Protocol, or MCP, the standard through which AI assistants like Claude talk to an ERP. Microtech has published open guides for it on GitHub, called skills, which explain to an assistant how Büro+ is structured and how a transaction comes about.

One thing is true for all three options: data goes to an AI. The difference lies in which data, who controls it, and what happens before anything is posted.

Three options for AI automation, compared

The three routes differ on three points: how long it takes to go live, how much of your data the AI sees, and whether anyone checks before it posts.

Option 1: Connect an AI assistant directly over the GraphQL API

An AI assistant on the ERP is connected within hours to days and suits analysis, not processes.

You connect an assistant like Claude over MCP to the GraphQL API of Microtech Büro+ ERP and ask your ERP questions in plain language. Which customers ordered a lot in August and nothing this month? The answer comes from live data. The first time it runs, it is impressive.

The catch: the assistant can do everything the linked user can do, and it decides for itself which data it pulls to answer a question. Whoever operates it sees terms, payment behaviour and transactions of every customer without ever logging into the ERP. If it writes a transaction, nobody checks the item number first. For one query a day that does not matter. For a hundred orders it does.

For a five-person business where the owner knows all the numbers anyway, it is a useful tool. A way to automate a process it is not.

Option 2: The custom build

A custom build is worth it when your process exists with no vendor. It costs months to go live and stays your maintenance job afterwards.

Your developers build their own application on the GraphQL API, tailored exactly to your process. That is the right call when your process is truly unique. Companies with a process like that usually know it.

What gets underestimated is rarely the connection but everything after it. Orders arrive in a hundred layouts, product descriptions have to become item numbers, and the ten percent of edge cases eat eighty percent of the time. And what you have built, you maintain: new AI models, new customer forms, the developer who knows it all leaves. For order entry, that means solving a solved problem a second time.

Option 3: A standard solution for the sales back office

A standard solution already brings proven use cases for Microtech Büro+ ERP and goes live within a few weeks, because the connection and the checking logic are already there.

Workist is an official Microtech partner and connects over the same GraphQL API, reading and writing, with no changes to your system.

What you get are proven use cases running at more than 200 companies. The Order Agent reads orders and price enquiries, checks them against your master data and creates orders or quotes. The Inbox Agent answers customer enquiries straight from the mailbox. The Voice Agent takes orders over the phone. Every case is checked before posting: what is unambiguous goes through, what is not goes to a person for approval.

And beside them stands Worki, the AI assistant inside Workist. It answers questions about your data and takes on, in chat, whatever does not fit a standard case: drafting a follow-up to a customer, tidying master data, resolving an edge case. The same flexibility as in option 1, but within the access rights you have set for Workist, and with a record of who did what.

That is why most companies end up here. The standard cases run checked and without your involvement, and for everything else there is an assistant that knows your ERP. Data protection is also easiest to establish this way: Workist is a processor under contract, access is limited to the back office, and every step is documented.

Which route fits you?

If you are up to ten people, everyone sees everything anyway and a handful of documents arrive each day, plug in an AI assistant.

If your process exists nowhere else, you have your own developers and you are prepared to maintain it for years, build it yourself.

If orders, enquiries and calls come into your back office every day, take a standard solution. You get the proven cases right away and the flexible assistant on top, without handing over a master key to do it.

Which concrete tools are available for that route is covered in our comparison of five AI tools for Microtech Büro+ ERP.

Frequently asked questions about AI in Microtech Büro+ ERP

Does Büro+ need to run in the cloud for AI to reach it?

No. The GraphQL API works on your own server just as it does in a private cloud. Workist connects the same way in both cases.

Can AI write through the GraphQL API as well as read?

Yes. Creating addresses, posting transactions, changing records, all of it is possible. What an access may do is set by you in Microtech Büro+ ERP. The difference between the three options is whether anyone checks before it writes.

Which processes in Microtech Büro+ ERP can Workist automate?

Creating orders and quotes from emails and PDFs, answering price and availability enquiries, taking orders over the phone, plus ad-hoc tasks via Worki such as follow-ups and master data maintenance. You will find an overview on the AI platform page for Microtech Büro+.

What sets Worki apart from an AI assistant plugged straight into the GraphQL API?

The boundaries. Worki works with the same master data and access rights as the standard agents, knows your articles and customers, and logs what it does. A directly connected assistant sees everything the linked user sees, and nobody checks what it writes.

Does data go to an AI with Workist?

Yes, as with any AI solution. The difference: Workist only receives the data the back office process needs, is contractually bound as a processor and is SOC 2 Type 2 certified. Customer data is not used to train public models.

Does Workist require changes to my Microtech Büro+ ERP?

No. The connection runs over the GraphQL API, with no middleware and no changes inside your tenant. You set up an access for Workist, nothing more.

How long does connecting to Microtech Büro+ ERP take?

A few weeks. The connection itself is standard; most of the time goes into your master data and agreeing which cases may run through automatically.

What does a custom build actually cost?

The connection is the smaller part. The effort sits in document capture, master data matching, edge cases and permanent maintenance as customer forms and AI models change.

Can the three options be combined?

Yes. If you use Workist, though, the back office no longer needs a second assistant, because Worki covers the ad-hoc cases. A directly connected assistant still makes sense for management reporting.

Read on: The AI platform for sales teams working with Microtech Büro+.