Overview
Our pipeline is modular, letting customers plug in at whatever stage matches their maturity level. From raw data ingestion through evaluation and monitoring, every stage is designed for transparency, reproducibility, and quality.
Pipeline Stages
- Data Ingestion & Profiling — Automated schema detection, statistical profiling, data quality scoring
- Categorization & Tagging Engine — Multi-label taxonomy, confidence scoring, difficulty gradient computation
- Annotation Orchestration — Human-in-the-loop workflows with active learning prioritization and consensus tracking
- Training Configuration & Execution — Hyperparameter sweeps, curriculum learning, dynamic negative sampling
- Evaluation & Monitoring Dashboard — Calibration curves, per-class breakdowns, gradient health, drift detection
Key Capabilities
- Automated data quality health reports
- Provenance tracking for every sample
- Multi-annotator consensus (kappa metrics)
- Programmatic weak-labeling integration
- Focal loss tuning and ratio optimization
- Real-time performance monitoring
Service Tiers
Self-Serve
API access to the pipeline with usage-based billing per compute-hour and per-annotation-task.
Managed
Dedicated pipeline instances with SLA guarantees, priority queuing, and technical support.
Enterprise
On-premise or VPC deployment, custom module development, and embedded engineering support.