Services
MLOps and inference infrastructure
A model registry, reproducible training runs and inference that holds the load.
We put the model lifecycle in order: where the weights live, how to reproduce a training run, how to roll out a new version without downtime. We build a GPU inference layer with stream balancing, artifact versioning and per-node metrics.
What the work includes
- Model registry and artifact versioning
- Reproducible training and evaluation pipelines
- Inference optimization for the available GPUs
- Latency, utilization and quality monitoring in production
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 moreData labeling and preparation
Production-grade datasets with annotator agreement under control.
Learn more