RSNA Cloud Connect deployed Amazon Connect for an entertainment industry client, migrating contact center routing, agent workflows, and analytics onto AWS with zero production disruption, zero critical defects, and all milestone gates passed.
Case Study Detail
| Company name | Single Source International |
|---|---|
| Case Study Title (Max 80 characters) | Amazon Connect Modernizes an Entertainment Company's Contact Center |
| Case Study Short Description (300 chars) | RSNA Cloud Connect deployed Amazon Connect for an entertainment industry client, migrating contact center routing, agent workflows, and analytics onto AWS with zero production disruption, zero critical defects, and all milestone gates passed. |
| Public or Private | Private |
ABOUT THE COMPANY
| Customer AWS Account ID | Not yet provided, required field, still blank |
|---|---|
| AWS Sales / PDM / Account Manager Assigned | Not yet provided, required field, still blank |
| AWS Solution Architect Assigned | Not yet provided, required field, still blank |
| Country of Work | United States |
| Start Date of Project | 6/1/2026 |
| End Date of Project | 7/10/2026 |
Problem Statement / Definition
The client’s legacy contact center platform constrained routing flexibility, native analytics, and agent experience for its guest and customer service operations. Leadership needed to modernize onto Amazon Connect without disrupting live production call volume and needed a clear, governed decision on which CRM, telephony, and AI capabilities to build immediately versus in a later phase.
Proposed Solution & Architecture
A parallel-run deployment of Amazon Connect covering agent seats, launched alongside the legacy platform to ensure a safe cutover. The build included an Amazon Connect instance with queues, routing profiles, and representative inbound contact flows (DID routing, overflow control, business-hours/holiday logic, transfers, and callback handling); the native Connect agent workspace with structured agent training; Contact Lens for real-time and historical analytics dashboards; and a security baseline of least-privilege AWS IAM roles, encryption at rest and in transit, and AWS CloudWatch monitoring. CRM (Salesforce CTI), telephony/SBC interconnect, and AI (Lex/Bedrock) integrations were evaluated against readiness criteria and sequenced into a phased roadmap.
Inbound contact flows
DID · overflow · callbacks
Amazon Connect
Queues · routing profiles
Agent workspace
Trained pilot population
Contact Lens
Analytics · CloudWatch
Outcomes of Project & Success Metrics
- Delivered on schedule with no slip against the committed plan
- All committed baseline deliverables completed and accepted
- All milestone gates passed
- Agent seats configured and trained for the pilot population
- Representative routing scenarios validated end-to-end against the legacy platform
- No open critical or high-severity defects at launch; remaining low-severity items resolved or deferred with documented disposition
- Steering Committee approved go-live and a phased roadmap
Describe TCO Analysis Performed
Implementation was funded through a combination of standard AWS partner funding and RSNA Cloud Connect delivery funding, with no direct cost to the customer prospect. AWS service usage costs for the environment were tracked separately in a companion AWS Cost Estimator workbook. Full ongoing operational TCO is being scoped as part of the next phase of planning.
Lessons Learned
Separating committed baseline scope from conditional integration scope — through a mandatory technical discussion requiring a named owner, approved architecture, access, test data, and acceptance criteria for each integration — kept CRM, telephony, and AI readiness gaps from putting the delivery timeline at risk. Running the deployment in parallel with a tested rollback path allowed full validation of routing and agent readiness with zero exposure to live production call volume for the customer prospect. Cross-training a secondary resource removed key-person dependency, and freezing the build ahead of testing protected a full, uncompressed testing window before go-live.
Separating committed baseline scope from conditional integration scope — through a mandatory technical discussion requiring a named owner, approved architecture, access, test data, and acceptance criteria for each integration — kept CRM, telephony, and AI readiness gaps from putting the delivery timeline at risk. Running the deployment in parallel with a tested rollback path allowed full validation of routing and agent readiness with zero exposure to live production call volume for the customer prospect. Cross-training a secondary resource removed key-person dependency, and freezing the build ahead of testing protected a full, uncompressed testing window before go-live.
Classification
| Industry Vertical | Digital Media; Media & Entertainment |
|---|---|
| Industry (Other) | Not applicable — covered by Industry Vertical above |
| Use Case | Business Applications; Data and Analytics; Disaster Recovery |
| Permission to contact customer? | No (unchecked) |
| New Implementation or Migration from another Solution? | New Migration |
| Other Solution | Legacy on-premises contact center platform |
| ISV Tools / Technology Used | None — native AWS services only (Amazon Connect, Contact Lens, AWS IAM, AWS CloudWatch); no third-party ISV tools were part of the delivered scope |
Reference / Architectural Diagram
Required upload
Required upload — not yet attached to either upload slot. This still needs to be created and attached before submission.
Tag Related Services / Programs / Competencies (Updated Selections)
✓ Amazon Connect is now correctly included in Related Services — this matches the delivery report.
✓ Related Programs (Managed Service, Well Architected Program) both align with the delivered solution’s security baseline and support model.
⚠ Amazon API Gateway still isn’t mentioned anywhere in the delivery report — the solution used Amazon Connect, Contact Lens, AWS IAM, and AWS CloudWatch only. Consider removing it, or swap in AWS CloudTrail/AWS CloudFormation if either was actually used for the pilot environment build.
⚠ Machine learning competency still doesn’t match—the delivery report explicitly defers Lex/Bedrock (the AI/ML components) to Phase 2. Nothing ML-related shipped in this delivery. Cloud operations software is a good fit and can stay; machine learning should likely be removed unless there’s ML work outside this report.
Outstanding Items Before Submission
- Customer AWS Account ID — required, not yet entered
- AWS Sales / PDM / Account Manager Assigned — required, not yet entered
- AWS Solution Architect Assigned — required, not yet entered
- Reference/architectural diagram file — required upload, not yet attached
- Related Services: consider removing Amazon API Gateway (see flag above)
- Related Competencies: consider removing Machine Learning (see flag above)