AI Architecture & MLOps Engineering

Scalable AI platforms with governed data pipelines and production-grade MLOps frameworks.

Reference Architecture

End-to-end AI platform including ingestion, feature engineering, orchestration, registry, and scalable inference.

Core Capabilities

  • Data ingestion & ETL pipelines
  • Feature store architecture
  • MLflow / Kubeflow lifecycle automation
  • Distributed training infrastructure
  • Model registry & governance
  • Secure AI platform design

Focus Areas

  • Regulated AI systems
  • Explainability & model risk governance
  • Real-time scoring pipelines
  • Enterprise AI modernization