AI development · Amsterdam, Netherlands

Good AI needs good software around it.

We design and develop AI-enabled applications, agents and knowledge systems from the interface through to integration, evaluation and deployment.

Discuss AI development

What has to work around the model for the product to be useful?

A model response is one part of the experience. Someone needs to sign in, find the right information, understand the result and act safely. The system also needs to survive timeouts, missing data and a provider update. We treat those conditions as product requirements.

WHAT YOU RECEIVE

Product designs, a technical architecture, application code, integration documentation, evaluation cases and a deployment and support plan.

01

Product and workflow design

Map the user’s task, decisions and exceptions before designing the interface. Define what a successful result looks like and which parts of the work should stay manual.

02

AI and retrieval engineering

Select models, structure context and connect approved knowledge. Build evaluation examples for accuracy, source relevance, uncertainty and out-of-scope requests.

03

Application and integration engineering

Implement interfaces, APIs, authentication and background work. Connect the surrounding systems using scoped credentials, explicit validation and recoverable operations.

04

Production delivery

Test the complete workflow, establish monitoring and release it with a handover plan. Record the dependencies, operating costs and procedure for changing or rolling back a release.

  • ✓Task-specific acceptance criteria
  • ✓Independent validation of model outputs
  • ✓Safe failure and retry behaviour
  • ✓Documented deployment and handover

A little more clarity.

A few questions worth asking before you build.

Talk through your project
Do you build an entire application or only the AI component?

Both are possible. The scope can cover a complete product or a defined AI capability inside existing software. Interfaces and ownership are agreed at the beginning.

How is scope estimated?

The main variables are workflow complexity, data quality, integrations, access controls, user experience and production requirements. A short discovery can turn an uncertain brief into a defensible scope.

What should AI do
for your business?

Tell us what you want to build, connect or improve.
We’ll help define the architecture, the delivery and what it takes to run it.

Bitsy answers from the heart — try one

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