Cloud Solutions & Services

Delivering Scalable, Secure, and High-Performance Cloud Architectures on AWS and Beyond

‍Aptus Data Labs helps enterprises harness the true power of the cloud through intelligent architecture, scalable automation, and cost-efficient AI/ML deployment. Our considered focus on Amazon Web Services (AWS) ensures high-performance delivery of data-driven, ML/AI enabled platforms with a clear line of sight to business value and total cost of ownership(TCO).

Our AWS-Centric Cloud Strategy

Our cloud strategy is built around delivering future-ready, cost-optimized architectures on AWS, from greenfield
cloud-native systems to legacy modernization and multi-layered AI transformation.
Whether you're starting small or scaling AI across the enterprise, we design for agility,governance, and measurable ROI.

Core Cloud Solutions

Cloud Architecture & Migration
Cloud-Native Development
Data & AI Workloads on AWS
Cloud Security & Governance
Cloud Optimization & TCO Management
Cloud Support & Managed Services
Hybrid & Multi-Cloud Expertise
  • Current-state infrastructure & workload assessment
  • Cloud-native re-platforming: containerization, microservices, decoupled storage
  • TCO modeling & migration strategy:
    • o Right-sizing compute/storage (EC2, S3, EBS)
    • Cost simulation using AWS Pricing Calculator and TCO Calculator
    • Savings Plans, Reserved Instances, and spot instances
  • Multi-account structure, landing zones, and security-first blueprints
  • Build event-driven microservices (Lambda, ECS, EKS)
  • RESTful & GraphQL APIs (API Gateway, AppSync)
  • End-to-end CI/CD with CodePipeline, CodeBuild, CloudFormation
  • Scalable pipelines for ingestion, transformation, and orchestration

Data Platform Engineering

  • Modern data lake/lakehouse creation using S3, Redshift, Glue, Lake Formation
  • Serverless querying and log analytics using Athena, OpenSearch

Machine Learning & Deep Learning

  • Full-lifecycle AI/ML development on Amazon SageMaker
  • Hyperparameter tuning, model training, monitoring, and shadow deployment
  • Managed feature stores and pipeline automation

MLOps & LLMOps

  • MLOps: Model versioning, lineage, CI/CD integration, A/B testing, and rollbackusing SageMaker Pipelines, MLflow, or Vertex Pipelines
  • LLMOps: RAG architecture, prompt tuning, fine-tuning pipelines, LLM versioncontrol, secure token management, and feedback loop integration
  • Monitoring for bias, drift, hallucination, and LLM grounding with AWS-native observability and third-party integrations

Generative & Agentic AI

  • Integration with Amazon Bedrock: Support for Claude, Titan, Jurassic, and StabilityAI models
  • Deployment of open-source LLMs (LLaMA, Mistral, Falcon) on SageMaker, EKS,or EC2
  • Enable Agentic AI for intelligent task automation across data pipelines, documentworkflows, and customer service
  • IAM role-based access controls and multi-factor authentication
  • VPC security design, traffic inspection, and encryption
  • Threat detection using GuardDuty, Inspector, and CloudTrail
  • Policy management and automated compliance via Config, Macie
  • Cost visibility using AWS Budgets, Cost Explorer, Trusted Advisor
  • Reserved Instances vs. On-Demand planning based on utilization metrics
  • Savings plan modeling for steady-state workloads
  • Auto-scaling configuration for dynamic load handling
  • TCO Dashboards with usage trends, ROI calculations, and optimization recommendations
  • 24x7 DevOps & CloudOps support with automated alerts
  • Infrastructure as Code (IaC) using CloudFormation, Terraform
  • SLA-based managed services for data platforms and ML pipelines
  • Ongoing model maintenance, drift detection, retraining, and support
We enable AWS-first strategies that integrate with on-premise, Azure, and GCP ecosystemsusing service mesh architectures and platform-agnostic DevSecOps pipelines for full workloadportability and governance.

Business Value Delivered by Aptus Data Labs

01
3x faster AI deployment with MLOps & LLMOps best practices
02
25–40% reduction in cloud TCO with continuous cost optimization
03
99.99% availability for mission-critical data pipelines
04
Full compliance with GDPR, HIPAA, and industry frameworks
Case Studies

Featured Success Stories

To build a scalable, secure, and analytics-ready Big Data platform to support advanced business intelligence, customer analytics, AML, segmentation, and other use cases—while optimizing existing infrastructure and unlocking the full value of enterprise data.
Big Data & Analytics Platform Implementation for Enhanced Business Performance in Banking

100% to 300% Improvement in Query Performance

Migration of 700+ TB Across 12,000+ Tables

USD 15+ Million ROI from Phase 1 Implementation

99.6% SLA Achieved with 24x7 Platform Support

To minimize scrap (initially at 21%) and enhance ADY% (production efficiency initially at 79%) using a consolidated BI & analytics platform with integrated ML models, real-time reporting, and on-demand data availability.
BI & Analytics Platform to Improve ADY% and Reduce Scrap in Telecom Manufacturing

200% Improvement in Model Execution Performance

Enhanced ADY% and Scrap Reduction

Integrated Reporting with Real-Time Dashboards

Always-On Platform Support

To build an ML-driven predictive pricing engine that could accurately forecast monthly supply, demand, and pricing for different food product categories, improve decision-making, and reduce time and cost spent on manual estimations.
ML-Based Price Prediction Engine for Optimizing Supply, Demand, and Pricing

Automated Optimal Price Estimation

Improved Forecasting Efficiency

CI/CD Enabled Retraining Pipeline

Cost and Time Savings Through Automation

To enhance regulatory adherence, document clarity, and operational efficiency by implementing an AI-based web platform for SOP evaluation and rewriting—addressing variability, complex language, and manual review bottlenecks in Biocon’s document processes.
AI-Powered SOP Rewriting Interface for Regulatory Compliance and Document Quality

Streamlined SOP Rewriting and Review Workflow

Improved SOP Quality and Readability

Audit-Ready Change Traceability

Foundation for AI-Enabled Regulatory Compliance at Scale

To automate and digitize the process of updating medicine preparation templates by replacing placeholder text with meaningful chemical and process information—eliminating manual effort, reducing human error, and speeding up processing across large volumes of documents.
Automated Placeholder Document Creation for Digitization of Pharma Templates

95% Reduction in Manual Effort

90–95% Accuracy in Placeholder Text Replacement

Drastic Time Reduction

Significant Cost Savings

See More Success Stories

Our integrated offering

Data Foundation & Value Management
Production Deployment & Support Enablement
Modernization & Migration Factory

Build Your Cloud-Native AI Future with Aptus Data Labs.

Accelerate your AI transformation, streamline operations, and optimize every cloud dollar with Aptus Data Labs and Cloud Partners.
Talk to our cloud Experts

Reach out to our Consultants,
Data and AI Practioners

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