Case studies
Selected client work.
Work across AI & Agents, Data & Cloud and Product Engineering for mid-market and enterprise companies worldwide.
- Case studies
- 20
- Industries
- 9
- Practices
- 3
Cutting an EU hotel group's agency staffing spend by 70%
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Questions
Still have questions?
What does a data project cost?
Cost follows scope: the systems to connect, how mature the current data layer is, how much review is needed and how long the team stays. Discovery takes two to four weeks and a first data product six to twelve. A proposal follows within a week of the first call.
How soon can work start?
A thirty-minute call, a written proposal within seven days, and a discovery sprint of two to four weeks to confirm scope before the build.
Who owns what is built?
The client owns everything: source code, infrastructure as code, pipelines, models, evaluation datasets and documentation, handed over in full with training for the team.
Does the company need a data platform before starting with AI?
No. Twistag works with companies at any stage of maturity, and data preparation comes first wherever it is needed.
How does Twistag work with the internal team?
Inside the client’s own infrastructure and workflow, with shared backlogs, stand-ups and definition of done. Teams can be extended, or the work can be run end to end.
Can the internal team run the platform afterwards?
Yes. Build, train and transfer is one of Twistag’s operating principles: engineers pair during the build, every system is documented, and handover walkthroughs happen before the engagement ends.
Have a similar challenge?
Start with the work that should change first.
A thirty-minute call, then a one-page outline of how Twistag would approach it.
A senior lead replies within one working day.
