Cloud & Infrastructure Architecture
Comprehensive cloud strategy, MLOps architecture, and high-performance computing infrastructure for AI/ML workloads, scientific computing, and enterprise scale.
Request ConsultationEnterprise-Grade Infrastructure for Modern AI/ML Workloads
We design and implement cloud and hybrid infrastructure strategies that balance performance, cost, security, and compliance. From multi-cloud architecture to on-premise GPU clusters for sensitive data, we help you build the foundation for scalable AI/ML operations.
Our expertise spans cloud provider selection, MLOps pipeline design, high-performance computing infrastructure, cost optimization, and security compliance—particularly critical in healthcare and life sciences.
Our Infrastructure Services
Cloud & Hybrid Strategy
Navigate the complexity of choosing between AWS, GCP, Azure, or a multi-cloud approach. We design hybrid architectures that combine cloud flexibility with on-premise GPU clusters for sensitive data processing.
- Multi-cloud architecture design and vendor selection
- Hybrid cloud strategy for sensitive data (HIPAA, GxP compliant)
- On-premise GPU cluster design and procurement
- Cloud migration planning and execution
MLOps Pipeline Architecture
Design the full AI/ML lifecycle infrastructure from data ingestion to model deployment and monitoring. We build production-ready MLOps pipelines that enable rapid experimentation while maintaining reliability.
- End-to-end MLOps pipeline design (data → training → deployment)
- Feature engineering infrastructure and feature stores
- Model training orchestration (Kubeflow, MLflow, SageMaker)
- Model versioning, validation, and A/B testing infrastructure
- Real-time model serving and monitoring systems
High-Performance Computing (HPC)
Specialized infrastructure for large-scale scientific simulation and model training, central to computational chemistry, drug discovery, and AI research. We design HPC clusters optimized for your specific workloads.
- GPU cluster architecture for AI/ML training
- Distributed computing infrastructure for simulations
- Storage systems optimized for large scientific datasets
- Job scheduling and resource management (SLURM, PBS)
- Performance tuning for molecular dynamics and AI workloads
Essential Infrastructure Capabilities
Cost Optimization & Governance
A critical pain point for most organizations. We design systems to track cloud spend, automatically shut down idle resources, manage access control, and implement chargeback models.
- Cloud cost tracking and attribution systems
- Automated resource scaling and shutdown policies
- Reserved instance and spot instance strategies
- FinOps frameworks and chargeback models
Security & Compliance
Especially critical in healthcare and life sciences. We architect infrastructure with data privacy, regulatory compliance (HIPAA, GxP), and comprehensive audit trails built in from day one.
- HIPAA and GxP compliant infrastructure design
- Data encryption (at rest and in transit)
- Identity and access management (IAM) architecture
- Audit logging and compliance monitoring
- Security scanning and vulnerability management
Why Our Infrastructure Architecture Matters
Optimized Performance
Infrastructure tuned for your specific AI/ML workloads, not generic cloud setups.
Cost Efficiency
Reduce cloud spend by 30-50% through intelligent resource management and optimization.
Compliance Built-In
Security and regulatory compliance (HIPAA, GxP) designed into the infrastructure from the start.
Future-Proof Scalability
Infrastructure that scales with your data, models, and team—without costly re-architecture.
Our Infrastructure Implementation Process
Assessment & Strategy
We analyze your current infrastructure, workload requirements, compliance needs, and cost constraints to design an optimal cloud and hybrid strategy.
- Current infrastructure audit
- Workload analysis (compute, storage, network)
- Compliance requirements mapping
- Cost modeling and TCO analysis
Architecture Design & Implementation
We design detailed infrastructure architecture and implement MLOps pipelines, HPC clusters, and security controls tailored to your needs.
- Detailed infrastructure architecture diagrams
- MLOps pipeline implementation
- Cloud resource provisioning (IaC with Terraform)
- Security and compliance configuration
Optimization & Support
We continuously monitor performance, optimize costs, and provide ongoing support to ensure your infrastructure evolves with your needs.
- Performance monitoring and tuning
- Cost optimization and right-sizing
- Security audits and updates
- Team training and knowledge transfer
Real-World Applications
Pharmaceutical R&D
Challenge: Need to run large-scale molecular dynamics simulations while keeping sensitive compound data on-premise.
Solution: Hybrid cloud architecture with on-premise GPU cluster for sensitive simulations and cloud burst for non-sensitive workloads.
AI/ML Startup
Challenge: Rapidly scaling ML model training while controlling cloud costs and maintaining model versioning.
Solution: End-to-end MLOps pipeline with automated model training, versioning, and cost-optimized spot instance scheduling.
Healthcare Analytics
Challenge: Build HIPAA-compliant data pipeline for patient data analysis with full audit trails.
Solution: HIPAA-compliant AWS architecture with encrypted data lakes, secure model serving, and comprehensive audit logging.
Ready to Build World-Class Infrastructure?
Whether you're starting from scratch or optimizing existing infrastructure, we help you build the foundation for scalable, cost-effective, and compliant AI/ML operations.
Schedule Infrastructure Consultation