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How Switchboard, MD Uses Amazon Nova Sonic to Automate Real-Time Call Transcription in Clinical Contact Centers

Transforming Healthcare Communication: The Impact of Real-Time Transcription in Contact Centers

Revolutionizing Patient Engagement with AI Solutions

Streamlining Contact Center Operations: The Switchboard, MD Approach

Choosing an Accurate, Scalable, and Cost-Effective Transcription Model for Contact Center Automation

Architecture and Implementation: Building a Scalable Solution

Nova Sonic Integration: Real-Time Speech Processing

Why Serverless: Strategic Advantages for Healthcare Innovation

Conclusion: The Future of Healthcare Automation with Amazon Nova Sonic

About the Authors

Transforming Healthcare with Real-Time Transcription: A Case Study on Switchboard, MD

In the fast-paced world of healthcare, every conversation with a patient carries immense clinical and operational weight. To thrive in high-volume healthcare contact centers, accurate real-time transcription is not just beneficial—it’s essential. With the ability to streamline electronic medical record (EMR) matching and automate workflows, real-time transcription eases the burden of manual data entry, allowing staff to concentrate on meaningful patient interactions. In an era where healthcare systems strive to balance efficiency and empathy, this capability has become a cornerstone for delivering responsive, high-quality care at scale.

Introducing Switchboard, MD

Enter Switchboard, MD, a physician-led AI and data science company on a mission to restore the human connection in medicine. They emphasize patient engagement and improved outcomes while tackling inefficiencies and reducing staff burnout. By developing clinically relevant solutions, Switchboard facilitates better collaboration between providers and operators, enhancing experiences for both patients and healthcare staff. A notable highlight of their offerings is a transformative contact center solution powered by AI voice automation, real-time medical record matching, and actionable next steps. These innovations have significantly reduced queue times and call abandonment rates, proving beneficial for both healthcare providers and patients.

Key Outcomes Achieved

  • 75% reduction in queue times
  • 59% reduction in call abandonment rates

However, despite these impressive early successes, Switchboard faced a significant challenge: their initial transcription approach struggled to scale economically while maintaining the necessary accuracy for clinical workflows. The cost and word error rate (WER) were not just metrics but vital factors determining the scalability of their automation capabilities.

Addressing the Challenge of Accurate and Scalable Transcription

Need for Precision

In clinical settings, transcription accuracy is crucial. Errors can compromise EMR record matching and disrupt automated workflows, resulting in adverse patient outcomes. To achieve their goals, Switchboard needed a transcription solution that seamlessly combined high accuracy with sustainable costs.

They investigated various options, even considering open-source models like OpenAI’s Whisper model hosted locally. However, these alternatives posed trade-offs in terms of performance, cost, or integration complexity.

The Solution: Amazon Nova Sonic

After thorough testing, the Switchboard team found that Amazon Nova Sonic met their needs perfectly. Here’s why:

  • 80–90% lower transcription costs
  • A word error rate of only 4% on their proprietary dataset
  • Low-latency output compatible with real-time processing requirements

Furthermore, Nova Sonic seamlessly integrated into Switchboard’s existing architecture, facilitating quick deployment and minimizing engineering complexity. As a result, they were able to reduce manual transcription steps, allowing for accurate, real-time automation across thousands of patient interactions.

"Our vision is to restore the human connection in medicine by removing administrative barriers that get in the way of meaningful interaction. Nova Sonic gave us the speed and accuracy we needed to transcribe calls in real time—so our customers can focus on what truly matters: the patient conversation."
— Dr. Blake Anderson, Founder, CEO, and CTO, Switchboard, MD

Architecture and Implementation: A Technical Overview

Switchboard’s innovative architecture employs Amazon Connect to capture live audio from both patients and representatives. This audio is processed through Amazon Kinesis Video Streams, which handles real-time media conversion before sending it to containerized AWS Lambda functions. These functions then establish bidirectional streaming connections with Amazon Nova Sonic, enabling the transcription of separate audio streams for each participant in a conversation—ultimately reassembling these for a complete transcription record.

Key Features of Nova Sonic Integration

  1. Real-time speech processing: Its capability to separate and recombine speakers’ audio makes it ideal for healthcare applications.

  2. Configurable settings: Options to prioritize either transcription or speech generation based on needs, allowing for significant cost savings while retaining accuracy.

  3. Cost optimization flexibility: Lowering speech output tokens during transcription can lead to substantial cost reductions.

Leveraging Serverless Architecture for Healthcare Innovation

Switchboard’s choice to utilize a serverless architecture with Amazon services brings extensive benefits. This approach:

  • Maximizes operational efficiency while minimizing infrastructure maintenance.
  • Allows engineers to focus on developing clinical automation features rather than managing servers.
  • Provides built-in fault tolerance and high availability, essential for critical healthcare communications.

Scalability and Cost Efficiency

Switchboard’s event-driven architecture allows the system to scale from handling a handful to thousands of concurrent calls without undue strain. The pay-as-you-go billing model ensures that they only pay for the compute resources used—maximizing cost efficiency and eliminating the risk of resource over-provisioning.

Conclusion: A Blueprint for Healthcare Innovation

Switchboard, MD’s successful implementation of Amazon Nova Sonic demonstrates the potential of transcribing technology in transforming healthcare operations. By achieving remarkable cost reductions without compromising on clinical-grade accuracy, they’ve laid a sustainable groundwork for scalable, AI-powered patient interactions across the industry.

Their journey illustrates how healthcare organizations can integrate accuracy, speed, and efficiency into their operations—shaping the future of patient engagement and care one conversation at a time.

For organizations looking to explore similar solutions, transitioning to Amazon Bedrock and tools like Amazon Nova Sonic presents an exciting opportunity to harness the power of AI in redefining healthcare communication and outcomes.


About the Authors

  • Tanner Jones: Technical Account Manager at AWS with expertise in AI agents and multi-agent systems.
  • Anuj Jauhari: Sr. Product Marketing Manager at AWS, focused on generative AI solutions.
  • Jonathan Woods: Solutions Architect at AWS passionate about clear communication of transformative technology.
  • Nauman Zulfiqar: Senior Account Manager at AWS dedicated to building strong customer relationships and advocating for their success.

Explore Amazon Nova on the Amazon Bedrock console to start your journey toward improved healthcare automation.

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