MLOps Services

We move models from notebooks to live production systems with safe deployment methods. We help you release models with no downtime, test them in real settings, and split traffic for better control.

• REST/gRPC model serving APIs
• Canary & blue-green deployments
• Real-time and batch inference
• Auto-scaling with Kubernetes

We track model performance in production by watching data quality, feature changes, output drift, and key business numbers. We also set alerts and retraining triggers when needed.

• PSI, KS test, SHAP-based monitoring system
• Concept & covariate drift detection
• PagerDuty / Slack alert routing
• Automated retraining triggers

We store every training run in one place, including settings, results, files, and model history. This makes it easy to compare runs, move the best model forward, and roll back to older versions.

• MLflow / W&B / Neptune setup
• Model versioning & lineage tracking
• Metadata search & comparison UI
• Approval workflows

We create a the main feature store to reduce training and serving mismatch, make feature reuse easier, and keep offline training and online inference in sync.

• Feast / Tecton / Hopsworks setup
• Online & offline feature stores
• Feature freshness SLA management
• Cross-team feature sharing catalog

We bring ML into your CI/CD process with automated model checks, data checks, performance testing, and approval rules before any model goes live.

• GitHub Actions / GitLab CI for ML
• Model quality gates & thresholds
• Automated bias & fairness tests
• Staging environment promotion

We track every change in your data from the raw source to the final training set. This helps you recreate the exact training data used for any model.

• DVC data versioning setup system
• End-to-end data lineage graphs
• Dataset audit trails
• Schema evolution management system

We set up all the records, approval steps, model documents, explainability reports, and bias checks needed for safety and compliant ML use.

• Model cards & documentation
• SHAP / LIME explainability
• Bias detection & fairness tests
• GDPR / HIPAA / SOC 2 alignment

Are you starting from zero? We also design and build your full MLOps setup, including tool choice, platform structure, team process, and governance rules and regulations.

• Architecture blueprint
• Toolchain selection & evaluation
• Cloud cost modeling
• Team workflow design & training