Manthano AI builds annotation and machine-learning datasets in central Switzerland. Text, image, video, audio and 3D, plus the human feedback and evaluation work that language models need.
Patient reported chest pain on 14 March at Kantonsspital Winterthur.
Programmes and partners
One partner for the label work, the data it is built on, the application on top of it, and the option of generating the data rather than collecting it.
Human-labelled training data across text, image, video, audio and 3D, and the feedback layer for language models: preference data, written demonstrations, rubric scoring, red-teaming.
Custom AI-driven applications, taken from concept through to deployment by the team that labelled the data.
The work before training: cleaning, structuring and checking datasets so a model has something honest to learn from.
Rendered training data built in 3D instead of collected and labelled: for classes that are rare, expensive to photograph, or cannot leave the building.
The label types our annotator programme is staffed for: classic supervised labelling, and the feedback and evaluation work that language models need. If your task is not on this list, describe it and we will tell you honestly whether it fits.
Documents sorted into your own label set.
Names, places and quantities marked in place.
Polarity and intensity, per document or per span.
Whole-image labels against a fixed taxonomy.
Bounding boxes around every instance.
Pixel-level masks, one class per pixel.
Objects tracked frame by frame.
Speech to timed text, speakers separated.
Cuboids and points in lidar or depth data.
Two or more answers, ordered against a written rubric.
Gold answers written by someone who knows the domain.
One answer scored per criterion: instruction-following, accuracy, tone.
Each claim traced to its cited source, or marked unsupported.
Prompts and answers classified against your policy, with severity.
Adversarial prompts written by hand, with what broke recorded.
Tool calls and multi-step runs judged step by step.
| Healthcare and life sciences | Medical imaging, clinical data, pharmaceutical research |
|---|---|
| Financial services | Banking, insurance and fintech applications |
| Manufacturing and Industry 4.0 | Quality control, predictive maintenance, automation |
| Technology and software | Computer vision, NLP and AI product development |
| Retail and e-commerce | Product categorisation, customer behaviour analysis |
| Public sector and research | Universities, research centres and organisations that need data processed locally |
For clients with strict residency or privacy requirements, annotation and preparation can run inside Switzerland rather than offshore. Ask for it when you scope the project and we will confirm what is possible for your data.
Written while building the annotation practice.
Six questions and you walk away with a written brief, whether or not you work with us.
