Your systems can talk to each other. They just need a common language.
You close a deal in the CRM, issue the invoice in accounting and write to the client from email. The same thing three times, in three windows. Thanks to APIs, it doesn't have to be that way. And thanks to AI, connecting them is easier today than ever before.
An API is an agreed way for systems to pass information to each other.
An API (application programming interface) is a set of rules by which two programs exchange data. You use one every day without knowing it: when an app on your phone shows the weather, a map or an order status, it asks another system through an API.
With a person
At a government office, you don't walk into the archive. You submit a request at the counter on the prescribed form and get an answer.
With AI
The API is that counter. The system defines exactly what you can ask, in what form, and what you get back.
Pipedrive, Raynet and HubSpot all have APIs. So do most accounting and email systems. Technically, almost everything you use in your company can be connected. The only question is who builds the connection and keeps it running.
With AI, you don't just read through an API. You can act too.
Until now, APIs mainly moved data between systems: an order from the e-shop is written into the warehouse, a payment into accounting. AI uses them in two ways. The first is reading: through the API it finds current data, such as an order status or a client's history, and answers based on it, not on a guess.
The second way matters more: through an API, AI can act. Not just say what needs to be done, but do it. Create a deal, issue an invoice, send an email. Each such action is like a button in the system that AI is allowed to press. You decide which buttons it gets.
“A salesperson writes in the chat: ‘We closed a deal with Novák, 3 licenses.’ Through APIs, AI updates the deal status in the CRM, prepares an invoice in accounting and drafts a thank-you email to the client with the invoice attached. The salesperson just checks and confirms.”
Case study: Finance and admin“Our own invoicing assistant has been running since February 2026 and has 32 tools. Each tool is one action in a system that AI is allowed to take: from issuing an invoice to checking unpaid payments.”
Not every API is open to everyone.
There are four types. For management, they translate simply: who may access which data.
| TYPE | WHAT IT MEANS FOR THE COMPANY | EXAMPLE |
|---|---|---|
| Public | Anyone can use it, following the rules | Exchange rates, weather |
| Partner | Only for verified partners with a login | Connection to a supplier or bank |
| Internal | Only for your own systems | Your warehouse and your e-shop |
| Composite | One request reaches into several systems at once | Client overview from CRM and accounting |
In company integrations, we most often work with partner and internal APIs. That is where the valuable data is, and the data that needs protecting.
A connection without rules is an open window.
Once systems start talking, you need to set who may do what. Three basic rules apply to every connection.
- Authentication and permissions: only those who need the data can get to it.
- Encryption: data is protected in transit as well.
- Rate limits: neither an error nor misuse will overwhelm your system.
With a person
A new accountant gets access to invoices, not to the whole company's payroll.
With AI
An agent that prepares invoices sees deals and billing details. Not salaries or internal notes.
When you don't need AI
If a process never changes, for example every paid order always creates the same invoice, a plain connection without AI is enough. It is cheaper and more predictable.
AI makes sense where decisions are needed: what a client's email says, which deal it relates to, whether it is a complaint or a new order. The API gives systems a common language. AI adds judgment.
AI is not good at everything. A model creates a little with every answer and may not answer the same way twice. In the text of an email, that is an advantage. In the amount on an invoice, it is a mistake. Where there is only one correct answer and it can be described exactly, a plain rule or program belongs there.
And not every model suits every task. Before each connection, be clear about who does what:
Always the same process, for example a paid order and an invoice: a plain connection without AI.
Reading and sorting, for example what an email is about and who it is for: a small, inexpensive model.
Decisions with exceptions, for example a complaint: a stronger model or an agent with clear rules.
Calculations and amounts: a program. AI can explain the result, but doesn't calculate it.
For more on choosing a model, see the article The most expensive model for everything is the most expensive mistake.
Ask yourself
How many hours a week do your people spend retyping the same thing from one system to another?
