AI challenge

Extend existing software with agentic workflows

Not every product needs to become an AI-first product. Sometimes a single agentic workflow is exactly enough: an existing process in which software independently performs a few smart steps before a user takes over again.

Does this sound familiar?

Agentic workflows pay off most when an existing feature currently takes several manual or half-manual steps.

  1. A user has to take many intermediate steps

    Fetching, comparing and passing on information takes unnecessary interaction.

  2. The next step depends on context

    A fixed workflow is too rigid, but full human handling is not always necessary.

  3. The software already has usable APIs

    Many of the required actions already exist technically, but are now triggered by hand.

  4. Full autonomy is not required

    The workflow may run on its own until a logical checkpoint or decision moment.

Where do you want to be?

You want to make an existing workflow smarter without redesigning the rest of the product.

Handle more work automatically

Within clear boundaries, the workflow can gather information and take actions itself.

Existing software stays in charge

The agent uses current data, APIs, auth and business logic.

Autonomy stays controllable

Critical steps can be validated or put in front of a user.

Why does this happen?

Adding an agent to existing software is mainly an architecture question: how much freedom does it get and which existing rules stay in charge?

See how we approach this

The agent has to work within existing domain rules

AI should not re-implement existing business logic in a different way.

Tool use has to be safe

A wrong answer is different from a wrong write or delete action.

State has to stay explicit

Long workflows need to know what has already happened and what still has to happen.

Why 9to5 for this?

Agentic workflows sit where AI meets existing software. That is where our experience with software architecture, integrations and AI engineering comes together.

View cases

Building on what exists

The agent builds on existing systems and rules.

Autonomy within limits

Tools, permissions and human-in-the-loop are designed deliberately.

Built for production too

Retries, logging, state and error handling are part of the build.

What else fits your situation?