5

Automation Framework

Designed and deployed a cloud-native quoting engine for House of Juice that replaces spreadsheets with Lambda-powered workflows, hybrid DynamoDB + PostgreSQL storage, and real-time dashboards. HTML quotes now auto-generate in seconds, cutting manual effort and operational cost.

Strategic Automation Framework for Quote Lifecycle Management

Challenge

House of Juice’s event-service team relied on email threads and Excel sheets to price corporate activations. The manual process delayed responses, produced version-control mistakes, and provided no visibility into quote status.

Strategy

  • Architect a serverless, event-driven pipeline on AWS: API Gateway → Lambda → DynamoDB for hot reads, with periodic sync to PostgreSQL for reporting.
  • Generate print-ready HTML quotes on-the-fly to avoid PDF storage and bandwidth fees.
  • Build a React dashboard that surfaces quote cards, status buttons, and live metrics for managers.

Execution

  1. QuoteCalculator Lambda ingests form data, computes pricing tiers, and writes to DynamoDB (JSON) + PostgreSQL (relational).
  2. QuoteNotifications Lambda pulls DB entries, renders tailwind-styled HTML, emails clients, and updates dashboard cards via WebSocket.
  3. Cost-aware design: provisioned concurrency only during business hours, S3-cached assets, and IAM least privilege policies.
  4. CI/CD with AWS SAM pipelines and unit tests for price-rule integrity.

Outcomes

  • Turnaround time for a new quote dropped from >24 h to ≈2 min.
  • Managers gained live visibility into every quote’s lifecycle; no more stale spreadsheets.
  • Infrastructure spend stayed under $25 mo. on the AWS Free Tier plus spot allocations.
  • Error rate in quote data entry reduced 95 % through automated validation.

Key Capabilities Demonstrated

  • AWS serverless architecture & hybrid data modeling
  • Workflow automation and real-time dashboards
  • Cost-optimized engineering and resource governance