Pairing AWS Lambda with Deepgram's speech-to-text (STT) API enables a scalable, serverless transcription workflow that efficiently handles varying audio data loads without maintaining servers or incurring idle costs. The workflow triggers a Lambda function when audio files land in an S3 bucket, which then utilizes a presigned URL to call Deepgram’s /v1/listen endpoint for transcription and writes the results back to S3. This guide provides a step-by-step process to set up this system, highlighting its advantages, such as event-driven design, minimal and predictable costs, built-in resilience, and zero-operations scaling. It also covers key components like SQS for buffering, IAM roles for permissions, and using Deepgram for accurate and low-latency transcription. The architecture is designed for platform engineers and developers seeking a hands-off, scalable solution for audio transcription that leverages AWS's serverless capabilities.