Sold by: Xal Digital USA
End-to-end design and deployment of production-grade machine learning pipelines using Amazon SageMaker, enabling organizations to accelerate model development, training, and operationalization on fully managed cloud infrastructure. XalDigital establishes repeatable MLOps workflows aligned to AWS Well-Architected principles that move data science teams from experimentation to production with confidence.
Overview
The XD Data Science & AI/ML Model Training solution delivers a structured, end-to-end MLOps implementation built on Amazon SageMaker, transforming fragmented model development processes into a governed, repeatable, and scalable machine learning platform. Designed for data science teams and analytics organizations, this professional services engagement enables organizations to accelerate model delivery, improve reproducibility, and establish institutional ML capabilities that evolve with their analytical maturity. XalDigital leverages SageMaker Studio, SageMaker Pipelines, and SageMaker Model Registry to build complete model development workflows covering data preparation, feature engineering, distributed training, model evaluation, and deployment automation. AWS Glue handles data ingestion and transformation from diverse sources, while Amazon ECR manages containerized training environments and Amazon CloudWatch provides operational visibility across all pipeline stages. The solution supports supervised, unsupervised, and deep learning workloads, with architecture patterns adaptable to demand forecasting, fraud detection, churn prediction, computer vision, and NLP use cases. All MLOps implementations include model governance, experiment tracking, approval workflows, and SageMaker Model Monitor for production drift detection. This product relates to the following AWS Services: Amazon SageMaker, Amazon S3, AWS Glue, Amazon ECR, Amazon CloudWatch, AWS Step Functions, Amazon Redshift, and AWS IAM.
Highlights
- XalDigital implements complete machine learning pipelines using SageMaker Pipelines, SageMaker Studio, and SageMaker Model Registry—covering data ingestion, feature engineering, distributed training, model evaluation, and automated deployment. Standardized workflows reduce time-to-production and ensure model reproducibility across teams.
- Every implementation includes SageMaker Model Registry for versioned model governance, experiment tracking for reproducibility, approval workflows for controlled promotion, and SageMaker Model Monitor for production drift detection. Organizations gain institutional ML capabilities with full audit trails aligned to AWS Well-Architected ML best practices.
- Leverage Amazon SageMaker's managed compute for cost-efficient distributed training with automatic scaling, spot instance optimization, and containerized environments via Amazon ECR. AWS Glue handles enterprise data ingestion from diverse sources, enabling data science teams to focus on modeling—not infrastructure management.
Details
Sold by
Delivery method
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Pricing
Custom pricing options
Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Support
Vendor support
XalDigital provides the following support levels for this solution: • Discovery Workshop: Requirements gathering for ML use cases, data landscape, and team structure. • Implementation Support: AWS-certified ML specialists for pipeline design, SageMaker configuration, and MLOps workflow setup. • Post Go-Live Hypercare: 15 business days of stabilization including pipeline tuning, monitoring configuration, and team enablement. • Extended Support (separate contract): Ongoing model management, platform updates, new use case onboarding, and SLA-based incident response. • Documentation: MLOps runbooks, pipeline documentation, and role-based training materials included. Support Contact dispatch@xaldigital.com