AI challenge

Automate a business process with AI

Not every process gets better with a fully autonomous agent. Sometimes the best solution is regular automation with one smart AI step in between. We build the workflow that fits the process.

Does this sound familiar?

Processes with a lot of copying, checking, interpreting and passing on are a good fit.

  1. People move information between systems

    A large part of the work consists of reading, retyping or classifying.

  2. The same decision rules keep coming back

    A workflow usually follows a fixed pattern with a limited number of exceptions.

  3. Unstructured information blocks classic automation

    Emails, documents or free text first have to be interpreted.

  4. Existing software has to stay part of it

    You don't want to replace all current systems to make one process smarter.

Where do you want to be?

You don't want as much AI as possible. You want less manual work, fewer errors and a process that stays technically manageable.

Less repetitive work

Predictable or time-consuming steps are carried out automatically.

AI only where it adds something

Interpretation and unstructured information go to AI; fixed rules stay regular software.

People stay in control

Critical exceptions or decisions can deliberately stay with an employee.

Why does this happen?

AI automation works best when you first technically split the process into deterministic and non-deterministic steps.

See how we approach this

Not every step needs AI

Using a language model for fixed rules makes processes more expensive and less predictable.

Exceptions determine reliability

The system has to know when continuing automatically is not wise.

Integrations are part of the process

The workflow has to be able to read and write in the systems employees already use today.

Why 9to5 for this?

For us AI is one tool within software automation. So we don't make a process artificially agentic when a simpler design is more reliable.

View cases

Process before technology

The desired outcome determines which steps need AI.

Existing systems stay usable

Integrations prevent an automation from becoming yet another standalone system.

Human oversight is part of the design

We explicitly design where exceptions should go to an employee.

What else fits your situation?