MLOps & Data

Ship models to production with confidence

We build production ML infrastructure — automated pipelines, model registries, drift monitoring, and serving at scale — so your data science team can focus on models, not operations.

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Capabilities

End-to-end ML operations

Automated Training Pipelines

Kubeflow, Prefect, and Airflow pipelines that trigger on data drift, schedule, or git push — with full lineage tracking.

Model Registry & Versioning

MLflow-powered model registry with stage promotion, A/B traffic splitting, shadow deployments, and one-click rollback.

Drift Detection & Monitoring

Real-time data and model drift alerts, performance dashboards (Grafana), and automated retraining triggers.

Model Serving

High-throughput, low-latency serving with BentoML, Ray Serve, or Triton — on Kubernetes, AWS SageMaker, or serverless.

Governance & Compliance

Experiment reproducibility, data lineage, audit logs, and GDPR/SOC 2 aligned practices baked into every pipeline.

What we deliver

The full MLOps toolchain

We use best-of-breed open-source tools and cloud-native services, tailored to your existing infrastructure — no vendor lock-in, no black boxes.

  • Kubeflow / Prefect / Airflow
  • MLflow experiment tracking
  • Model registry + versioning
  • Drift detection & alerting
  • BentoML / Ray Serve
  • Shadow & canary deployments
  • Feature store (Feast / Tecton)
  • Grafana + Prometheus monitoring

Reference MLOps stack

OrchestrationKubeflow / Prefect
Experiment trackingMLflow
Feature storeFeast / Tecton
Model servingBentoML / Ray Serve
MonitoringGrafana + Evidently
InfraKubernetes / AWS / GCP
Pricing

Milestone-based engagements

Foundation

₹8,00,000

Core MLOps setup for a single ML workload.

  • CI/CD for models
  • MLflow tracking
  • Grafana dashboards
  • Drift alerts
  • 5-week delivery
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Platform

₹24,00,000

Full MLOps platform for multi-model organisations.

  • Multi-pipeline orchestration
  • Feature store
  • A/B & shadow deployments
  • Model serving cluster
  • Team training
  • 12-week delivery
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Enterprise

Custom

Managed MLOps for large-scale AI operations.

  • Custom cloud/on-prem
  • Governance & audit
  • Dedicated MLOps engineer
  • SLA support
  • Quarterly reviews
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Ready to productionise your models?

Talk to our MLOps engineers and get a tailored architecture recommendation.

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