Recurring work
The same kind of request, document or comparison comes up regularly.
Case studies
AI in day-to-day work.
Applications for finance, operations, support and existing products. These projects show the task, connected systems and where people stay involved.
Areas
Concrete tasks. Different environments.
Explore how each application processes information, prepares a result and hands work back to the team.
Process documents and data
Read information from documents, combine sources and prepare records for the next step.
Connect recurring workflows
Reconcile records across systems, prepare responses and hand exceptions to the right person.
Invoice checks at babyartikel.de
The application compares invoices with goods receipts, prices and terms. Deviations are flagged for the team to review.
View casePrepare answers with researched context
A digital support employee that structures requests, uses knowledge sources, and prepares responses for approval.
View caseBuild AI into products
Turn product data into useful outputs, with the terminology and rules your application needs.
AI Sleep Coach for sleep²
An in-product AI system that generates tens of thousands of Sleep Analysis Cards every day in more than 15 languages and follows the Sleep2 glossary.
View caseKolloqo for IRC Consult
An AI interview system that makes structured interviews more dialogic and prepares answers for questionnaire processes.
View caseFit
What makes a useful starting point?
A process does not need to be perfect. It needs a clear scope and people who can judge the result.
Accessible information
Relevant data can be made available through agreed interfaces and permissions.
Reviewable outcomes
Your team can identify correct results and decide what happens with exceptions.
Classification
Start with the workflow and its boundaries.
Every project connects a defined task with available data and systems. The useful level of automation depends on the workflow and the decisions people need to retain.
We use this context to assess a new use case with you. Results from one project are not a performance promise for another.
Next step
Would you like to check a similar process?
Tell us about the workflow and systems involved. We will discuss a useful next step together.
Discuss your use case