Amazon SageMaker Job Support — Unified Data & AI Development on AWS

The next generation of Amazon SageMaker is a unified platform for data and AI, centered on SageMaker Unified Studio, with SageMaker Lakehouse (data), SageMaker Catalog (governance), and integrations across EMR, Glue, Athena, Redshift, and Bedrock. SageMaker AI is the machine-learning capability within that platform — training, tuning, deployment, MLOps, and inference (formerly the core "Amazon SageMaker" ML service). We support both and help you use them together.

Setting up and using SageMaker Unified Studio and projects, configuring Lakehouse over S3 and Redshift on Apache Iceberg, governing data and models with SageMaker Catalog and Lake Formation, integrating Bedrock and SageMaker AI, wiring IAM Identity Center, and building end-to-end data-and-AI workflows. We also handle production issues and architecture reviews.

Yes. We help you configure SageMaker Lakehouse for unified access across S3 data lakes, Redshift warehouses, and federated sources using Apache Iceberg, enable zero-ETL patterns where supported, and set up SageMaker Catalog for data-asset and model discovery, metadata, lineage, and access governance with Lake Formation.

Yes. Unified Studio project and permissions issues, Lakehouse access and federation problems, Catalog governance and lineage gaps, and SageMaker AI training/inference failures — we work these live. See our SageMaker AI and inference troubleshooting pages for the ML-specific incidents.

Message us on WhatsApp with your SageMaker setup and where you are stuck. We assign the right expert — usually same-day. Every engagement is confidential and NDAs are available.