ThriveAssist End-to-End AI Processing Pipeline orchestrates audio intake through secure upload, transcription, language detection, and AI-driven assessment using AWS Lambda, Amazon Transcribe, Amazon Comprehend, and Claude models via Amazon Bedrock. Audio files flow from the Thrive Mobile App through S3 buckets, triggering Lambda functions that coordinate transcription, real-time notifications via SQS/SNS, and language-aware translation and assessment. Amazon RDS persists metadata and AI recommendations while asynchronous notifications keep caseworkers updated throughout the pipeline. This architecture demonstrates event-driven data processing with managed AI services, reducing operational overhead while maintaining audit trails and real-time visibility. Fork this diagram on Diagrams.so to customize Lambda triggers, add additional AI models, or integrate with your own notification systems. The pattern separates concerns across discrete Lambda functions, enabling independent scaling and failure isolation for each processing stage.