Solutions by industry
Data work shaped around how your AI is used.
A self-driving stack, a medical chatbot and a shopping search engine need very different data. Here is how we help teams in each space.
Across the AI lifecycle
One partner from first dataset to final evaluation.
Most teams need more than one kind of data work. Because we cover collection, annotation, fine-tuning data and evaluation, your guidelines and quality standards carry through every stage.
01 · COLLECT
Source the data
Custom collection to your brief and consent rules.
02 · LABEL
Add meaning
Annotation and QA to clear, shared guidelines.
03 · TRAIN
Teach the model
SFT and preference data written by people who know the task.
04 · EVALUATE
Check the results
Human evaluation and red teaming before you ship.
Start with your use case