Amazon Transcribe Call Analytics

Improve customer experience with real-time ML-powered conversation insights

Amazon Transcribe Call Analytics is a generative AI-powered API for generating highly accurate call transcripts and extracting conversation insights to improve customer experience and enhance agent and supervisor productivity. The API combines powerful speech-to-text models, large language models (LLMs), and task-specific natural language processing (NLP) models that are trained to understand customer service and sales calls. 

With Amazon Transcribe Call Analytics, you get valuable intelligence such as customer and agent sentiment, call drivers, non-talk time, interruptions, and talk speed. The call categorization capability allows you to classify conversations based on custom criteria such as sentiment, competitive mentions and specific phrases like “not happy,” “poor quality,” and “cancel my subscription”. In addition, you can use generative-AI powered call summarization capability to deliver a concise summary of a customer interaction and capture key components such as why the customer called, how the issue was addressed, and what follow-up actions were identified. Further, the API can help you detect and redact sensitive information such as names, addresses, and credit card information from both the audio and text in real time or post-call. These capabilities help you to improve experiences for customers, agents, and supervisors in your contact centers.

Common use cases for Amazon Transcribe Call Analytics API include agent assist, supervisor alerts, agent scoring, call intent tracking, and post-call analytics.

Build an agent assist solution to improve call resolution & agent productivity (50:28)

How it works


Reduce implementation complexity

Transcribe Call Analytics makes it easier to put together a pipeline of multiple AI services and create dedicated ML models. You can add Transcribe Call Analytics as a single API output to any contact center or sales call application quickly, reducing implementation time.

Gain ML-powered insights

Transcribe Call Analytics comes with natural language processing (NLP) models that are pretrained on conversational data and optimized to provide accurate call transcripts and actionable insights that can improve customer experience and agent productivity. No ML expertise is needed to build, train, and maintain these models.

Use your existing contact center

You can use Transcribe Call Analytics to analyze and gain valuable real-time and post-call insights from the contact center of your choice. As an API, Transcribe Call Analytics gives you the flexibility to add these capabilities into call applications such as customer service, sales, and more.


Improve productivity in contact centers with generative AI-powered call summarization

Automatically generate call summaries to help agents focus on providing excellent customer experiences and increase productivity by reducing after-call manual summarization. This capability summarizes an interaction with a caller, capturing key components such as the reason for the call, steps taken to resolve issue, and next steps. Contact center supervisors can review call summaries to quickly understand the context of an interaction without reading the whole transcript while investigating caller issues.

Extract detailed call analytics and conversation insights

Using the power of ML, you can quickly apply speech-to-text and NLP capabilities during live calls and uncover valuable conversation insights. You can then integrate insights such as customer and agent sentiment, detected issues, and speech characteristics like non-talk time, interruptions, and talk speed into your inbound and outbound call analytics applications. This can help your supervisors more readily identify potential customer issues, agent coaching opportunities, product feedback, and call trends.

Improve compliance and monitoring with automated call categorization

Monitor your calls at scale to track compliance with company policies or regulatory requirements. Build and train your own custom categories based on your specified criteria (such as words/phrases or conversation characteristics). For example, you can set up category labels to see what percentage of calls are upsells or account cancellation.

Protect sensitive customer data

Conversations often contain sensitive customer data such as names, addresses, credit card numbers, and social security numbers. Transcribe Call Analytics helps you identify and redact this information from both the audio and the text.


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Get started with the Amazon Transcribe Call Analytics

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Learn more about pricing
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