This is a div block with a Webflow interaction that will be triggered when the heading is in the view.

Modernize your cloud. Maximize business impact.
Executive Summary
BeNotable is a platform dedicated to connecting music students with colleges. To stay ahead in a competitive landscape, BeNotable aimed to leverage Generative AI to enrich students’ audition experience and differentiate their service. We assessed their existing AWS-based data infrastructure (Amazon S3 and DynamoDB), technical maturity, and business objectives. The assessment highlighted an opportunity to introduce the “Aria Audition Lab Coach”, giving students instant, AI-generated feedback on tone, rhythm, and expressive quality. This case study outlines how we implemented a secure, scalable, and cost effective Generative AI workflow on AWS.
Challenges
- Provide high quality AI feedback on large volumes of audio while maintaining low latency.
- Protect student data and intellectual property with robust security controls.
- Ensure end to end observability and graceful failure handling across asynchronous workloads.
- Integrate seamlessly with BeNotable’s existing AWS foundations without disrupting live users.
Scope of the project
- Discovery & Readiness : Assessed data quality, security posture, and AI objectives.
- Architecture & PoC :Designed an event driven, serverless architecture and validated model choice in Amazon Bedrock.
- Implementation : Built secure upload, processing pipeline, AI inference, and feedback delivery using API Gateway, Lambda, S3, DynamoDB, SQS/SNS, and EventBridge.
- UAT & Launch : Performance, security, and user acceptance testing with staged rollout.
- Enablement:Delivered IaC templates, runbooks, and a roadmap for multilingual expansion.
Partner Solution
- Cloud native platform - That matches music students with colleges via audition submissions.
- Web and chatbot interfaces - For students to upload recordings and receive feedback.
- Existing AWS foundations - Amazon S3 for raw audio and Amazon DynamoDB for metadata storage.
- Key business goals - Deepen student engagement, enrich learning experience, and stand out from competitor platforms.
- Secure Upload – Students authenticate with Amazon Cognito; requests are filtered through AWS WAF and served via Amazon API Gateway to a “PUT /upload audio” Lambda function.
- Storage Layer – Raw recordings land in an Amazon S3 bucket; Lambda captures metadata (student, instrument, timestamp) and writes to Amazon DynamoDB.
- Processing Pipeline – An SQS queue triggers a processor Lambda that transcribes audio and invokes Amazon Bedrock (Anthropic Claude or AI21) to generate feedback. Events are coordinated with Amazon EventBridge.
- Messaging Layer – Results are published through Amazon SNS. A Dead Letter Queue retains failed messages for replay and root cause analysis.
- Observability & Monitoring – Amazon CloudWatch Logs, metrics, and AWS X Ray traces provided full visibility, while AWS Config & IAM manage compliance and least privilege access.
- Scalability & Resilience – The design is serverless and fully managed, automatically scaling with usage and isolating faults through queue based decoupling.
Solution Architecture Diagram

Metrics Used to Measure Success & Lessons Learned
- Engagement: +30 % increase in average session duration; 2× rise in audition uploads.
- Latency: p95 feedback delivery < 4 s.
- Reliability: < 0.2 % message failure, all captured in DLQ
- Cost Efficiency: ~40 % reduction in operational overhead via serverless pay per use.
Lesson Learned
- Prompt engineering with few shot and chain of thought examples is key to nuanced music feedback.
- RAG with Titan Embeddings grounds generative output in music theory references for factual accuracy.
- Comprehensive observability accelerates latency tuning and error resolution.
- Early educator feedback loops refine model prompts and sustain content authenticity.
Outcome (Business Impact)
- Students receive immediate, high quality feedback, increasing practice frequency and quality.
- Colleges gain richer audition insights, improving talent fit decisions and placement rates.
- BeNotable differentiates as an AI driven innovator, attracting new users and institutional partners.
- Serverless architecture scales elastically with peak audition seasons while aligning costs to usage.

Get started on your cloud modernization journey today!
Let Cloudtech build a modern AWS infrastructure that’s right for your business.