AI challenge

Add AI to existing software, an app or SaaS

You don't need to build a completely new AI product. Often most of the value lies in one smart feature inside software users already know. We make sure that feature fits the existing product technically.

Does this sound familiar?

The problem is usually not how to call a model, but how the new functionality should relate to the existing product.

  1. The feature needs existing product data

    AI has to work with users, documents or other information already in the product.

  2. Permissions must simply keep working

    AI must not suddenly expose information or actions that are protected elsewhere.

  3. The existing UX should stay in charge

    Users want a better workflow, not necessarily a chat interface.

  4. You don't want to rebuild the current product

    The AI layer has to connect to what already works well technically.

Where do you want to be?

The new AI functionality should feel like part of the product, not like a chatbot glued on later.

AI fits the existing user flow

The feature supports what users are already trying to do.

The existing architecture stays manageable

AI is integrated without needlessly adding a second technical world.

Production risks are covered

Costs, latency, errors and uncertain model behaviour get a place in the design.

Why does this happen?

Integrating a standalone AI API is easy. Designing AI as a reliable part of existing product software is another story.

See how we approach this

Existing software already has rules

Data, permissions, business logic and user expectations are largely fixed.

AI introduces other failure modes

Latency, incorrect output and variable costs have to be handled in existing flows.

The new feature can end up too detached

A separate AI system quickly leads to duplicated data and logic.

Why 9to5 for this?

Understanding and extending existing software is a big part of our work. So AI doesn't need a greenfield to be built well.

View cases

Understand the existing architecture first

We design the AI feature around what already works.

Integration over isolation

Data, auth and business logic are not duplicated unnecessarily.

Production from the design onwards

Reliability and operational consequences count before the feature goes live.

What else fits your situation?