AWS AI/ML Services
Deploy, manage, and optimise your AI and Machine Learning solutions on the AWS cloud platform. From SageMaker to Bedrock, we help you harness the full suite of AWS AI/ML services for scalable, secure deployments.
Why AWS for AI/ML?
AWS provides the broadest and deepest set of AI and ML services, with the infrastructure and tools to support every stage of your AI journey. Combined with Databricks on AWS, you get the best of both worlds: AWS's cloud infrastructure with Databricks's unified data and AI platform.
As an AWS partner, we help Australian enterprises design, build, and operate AI/ML solutions that meet strict performance, security, and compliance requirements including APRA, Privacy Act, and IRAP.
AI/ML services and features available on AWS
AWS regions for data sovereignty compliance
SLA availability for production workloads
Our AWS AI/ML Services
Comprehensive AI/ML solutions across the AWS ecosystem
- Custom model training with managed infrastructure
- SageMaker Studio for collaborative development
- Automated model tuning and hyperparameter optimisation
- Real-time and batch inference endpoints
- SageMaker Pipelines for MLOps automation
- Anthropic Claude, Meta Llama, and Amazon Titan models
- Knowledge bases for RAG applications
- Agents for complex multi-step tasks
- Fine-tuning with your proprietary data
- Enterprise security and data privacy built-in
- Amazon Comprehend for NLP and text analytics
- Amazon Rekognition for image and video analysis
- Amazon Forecast for time-series predictions
- Amazon Personalize for recommendation engines
- Amazon Textract for document processing
- Amazon S3 data lake architecture
- AWS Glue for data integration and ETL
- Amazon Redshift for analytics warehousing
- AWS Lake Formation for governance
- Databricks on AWS for unified data and AI
- GPU instance selection and optimisation
- Distributed training across multiple instances
- Cost-efficient spot instance strategies
- Auto-scaling inference infrastructure
- Edge deployment with AWS IoT Greengrass
- IAM policies for ML resource access
- VPC configuration for data isolation
- Encryption for data at rest and in transit
- AWS CloudTrail for audit logging
- Compliance with APRA, Privacy Act and IRAP
Databricks + AWS: Better Together
Combine the power of Databricks's unified data and AI platform with AWS's world-class cloud infrastructure for maximum impact.
Data Layer
- Databricks lakehouse on S3
- Unity Catalog for governance
- Delta Lake for reliable data pipelines
AI/ML Layer
- SageMaker for model training
- Bedrock for foundation models
- MLflow for model lifecycle
Implementation Approach
- Current infrastructure and workload analysis
- AWS service selection and architecture design
- Security, compliance, and cost optimisation planning
- Infrastructure provisioning with IaC (CloudFormation/Terraform)
- ML pipeline development and model training
- Deployment with monitoring and alerting
- Performance tuning and cost optimisation
- Automated scaling and operational excellence
- Team training and knowledge transfer
Build on AWS: Start Your AI Project
Let's design and deploy your AI/ML solution on AWS with enterprise-grade security and performance.