Sold by: DATAGENTIC AI
Our AWS Machine Learning Consulting Services delivers end-to-end AI/ML solutions from strategy and model development to production deployment and MLOps, leveraging Amazon SageMaker, AWS AI Services, and comprehensive responsible AI practices. We architect, train, and deploy production-grade machine learning models with automated MLOps pipelines, achieving 40-50% model accuracy improvements, <100ms inference latency, and 99.9% uptime. Our services include predictive analytics, computer vision, natural language processing, demand forecasting, fraud detection, and personalization with full model governance, bias detection, explainability, and continuous monitoring.
Overview
Accelerate AI Transformation with Production-Ready ML Solutions
AWS Machine Learning Consulting Services transforms your business challenges into measurable outcomes through production-ready AI/ML solutions built on Amazon SageMaker and AWS AI Services. We deliver complete ML lifecycle management from strategy and data engineering to model development, MLOps deployment, and continuous monitoring, solving critical business problems including predictive maintenance, fraud detection, customer churn prediction, computer vision quality control, intelligent document processing, demand forecasting, personalization, and recommendation systems. Our proven methodology achieves 40-50% model accuracy improvements, 60-70% reduction in development time, and measurable business impact including cost savings, revenue growth, and operational efficiency gains across financial services, healthcare, retail, manufacturing, and telecommunications industries.
Enterprise MLOps with Responsible AI and Governance
We implement enterprise-grade MLOps using Amazon SageMaker Pipelines, Feature Store, Model Registry, and Model Monitor integrated with AWS CodePipeline for automated CI/CD, achieving 99.9% model uptime, <100ms inference latency, and automated retraining with drift detection. Our responsible AI framework includes bias detection with SageMaker Clarify, model explainability, comprehensive model cards, audit logging with CloudTrail, and governance workflows ensuring fairness, transparency, and accountability. Solutions leverage AWS data services (S3, Glue, Athena, Kinesis, EMR, Lake Formation), AWS security services (IAM, KMS, VPC, Secrets Manager), and AWS AI Services (Rekognition, Comprehend, Textract, Forecast, Personalize, Lex, Kendra, Fraud Detector) delivering 50-60% cost savings versus on-premises infrastructure, complete infrastructure-as-code with CloudFormation, and positive ROI within 12-18 months with comprehensive training and knowledge transfer in 16-36 weeks.
Highlights
- Transform Business Challenges into AI Solutions - Solve critical business problems including predictive maintenance (35% downtime reduction), fraud detection (60% loss reduction), customer churn prediction (40% churn reduction), computer vision quality control (90% accuracy), and demand forecasting (25% inventory reduction) using Amazon SageMaker and AWS AI Services.
- Enterprise MLOps with 99.9% Uptime and <100ms Latency - Production-grade ML deployment with automated CI/CD pipelines, model monitoring, drift detection, and automated retraining using SageMaker Pipelines, Feature Store, Model Registry, and Model Monitor integrated with AWS CodePipeline achieving 60-70% faster time-to-production.
- Responsible AI with Bias Detection and Explainability - Comprehensive responsible AI framework with SageMaker Clarify for bias detection, SHAP and LIME for model explainability, model cards for transparency, audit logging with CloudTrail, and governance workflows ensuring fairness, accountability, and regulatory compliance.
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