AWS Cloud Solutions
AQBEE delivers complete AWS cloud development services — not just integration. From designing cloud-native architectures on EC2, Lambda, and ECS to building data lakes on S3 and Redshift, deploying AI/ML models on SageMaker, and creating serverless microservices, we handle the full lifecycle. Our AWS-certified architects build secure, scalable, cost-optimised solutions that work seamlessly with your Salesforce ecosystem.
What We Deliver
Salesforce-AWS Connector
Implement the Salesforce-AWS connector for real-time data exchange using Amazon EventBridge, enabling event-driven architectures between CRM and cloud workloads.
AI/ML Model Integration
Train custom ML models on Amazon SageMaker and deploy predictions into Salesforce workflows via Einstein AI or custom APIs for advanced use cases beyond native Einstein capabilities.
Data Lake & Analytics
Replicate Salesforce data to Amazon S3, Redshift, or Athena for advanced analytics, data science, and business intelligence workloads that complement Tableau and CRM Analytics.
Serverless Application Development
Build serverless microservices on AWS Lambda and API Gateway that extend Salesforce functionality — document processing, media conversion, and high-volume data processing.
Infrastructure & Security
Design VPC architectures, IAM policies, encryption, and compliance controls for Salesforce-AWS integrations that meet enterprise security and regulatory requirements.
How We Apply It
AI-Powered Document Processing Pipeline
An insurance company builds a document processing pipeline using Amazon Textract for OCR, SageMaker for classification, and routes extracted data into Service Cloud cases via MuleSoft — reducing manual processing by 80%.
Amazon Textract extracts text from claim documents, SageMaker custom models classify document types, and Einstein AI in Service Cloud auto-triages claims based on extracted data.
IoT Data Platform for Manufacturing
A manufacturer streams IoT sensor data through AWS IoT Core and Kinesis to Data Cloud, enabling real-time equipment monitoring dashboards and predictive maintenance workflows in Service Cloud.
Amazon SageMaker anomaly detection models identify equipment degradation patterns, triggering automated work orders in Salesforce Field Service.
High-Volume Data Processing for Financial Services
A bank processes millions of daily transactions through AWS Lambda and Step Functions, enriching records with fraud scores before loading into Financial Services Cloud for advisor visibility.
Amazon SageMaker real-time fraud detection models score transactions, with high-risk alerts routed directly to Service Cloud for investigation.
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