Data readiness
Cleaning, feature design, and split strategies that reduce drift and leakage.
Machine Learning Models
Custom ML models for predictions, recommendations, and scoring that tie to business KPIs.
We handle data prep, training, and evaluation, then deploy with monitoring so models stay healthy in production.
Model training
Classical ML or modern architectures chosen to fit signal, latency, and cost needs.
Deployment and MLOps
Versioned models, canary releases, and dashboards to watch accuracy over time.
What you can expect
Bias and fairness checks before models ship to production.
Reproducible pipelines with tracked experiments and metrics.
Alerts on drift, latency, and error rates with rollback paths.
Retraining playbooks tied to data freshness and KPI changes.