Expert training data
We turn professional knowledge into examples AI teams can use to train and improve their models. Our experts write realistic tasks, produce reference answers and correct model responses.
- Domain-specific tasks and reference answers
- Data annotations and classifications
- Response comparisons and preference ratings
- Corrections with supporting explanations
Each dataset is reviewed for accuracy, consistency and relevance to the intended use case.
AI model evaluation
Our experts test model responses for accuracy, reasoning and professional standards. We identify errors, explain their significance and provide feedback your team can use to improve the system.
- Scoring criteria for your use case
- Expert ratings supported by evidence
- Error analysis and corrected responses
- Evaluation reports for model comparison and development
Evaluation can support model selection, testing before deployment and ongoing performance review.
Expert selection and quality review
Match the expertise
Review professional experience and assess the specialist knowledge required for the project.
Prepare the reviewers
Test the instructions on a shared sample and resolve differences in interpretation before production.
Review the work
Check annotations and evaluations against the scoring criteria. Use additional expert review to resolve material disagreements.
Deliver the results
Provide structured data, review findings and documented limitations in the formats your team needs.
Canadian experts and project delivery
Our network is built around professionals working in Canada. Projects can use remote work or a controlled environment, depending on the task and the client’s requirements.
Before work begins, we confirm data access, permitted tools, storage, retention and ownership of the outputs. Data residency and other sovereign requirements are established for each project.
Discuss your AI data project
Tell us what your model needs to do and where expert input is needed.
Project enquiries