Services
Data labeling and preparation
Production-grade datasets with annotator agreement under control.
We collect, clean and label data for a specific task. We write annotator instructions, configure the tooling, measure agreement between annotators and re-check samples of the result. A poor dataset cannot be compensated by a good architecture, which is why we never cut this stage short.
What the work includes
- Instructions and reference examples for annotators
- Labeling tooling configured for the task type
- Agreement control and sampled quality audits
- Class balancing and handling of rare scenarios
Other services
Computer vision and video analytics
Real-time detection, tracking and event classification on existing cameras.
Learn moreLLM and natural language processing
Assistants, document data extraction and multimodal models for business tasks.
Learn morePredictive analytics and ML models
Demand, equipment failure and anomaly forecasting from historical and telemetry data.
Learn moreMLOps and inference infrastructure
A model registry, reproducible training runs and inference that holds the load.
Learn more