Awesome
AI Powered Call Center Intelligence Accelerator
The Call Center Intelligence Accelerator drives huge cost saving in call center operations while improving call center efficiency & customer satisfaction.
It uses Azure Speech, Azure Language and Azure OpenAI (GPT-3) services to analyze call center transcrips, extract and redact personally identifiable information (PII), summarize the transcription, and provides rich business insights that could be used in real-time. It delivers deeper business insights for managers and enables them to evaluate call center performance far more efficiently and effectively in real-time and batch scenarios. Data insight on customer sentiment, topic analysis, and other valuable call attributes are served up in a user-friendly visual dashboard in Power BI.
The diagram below depicts key business outcomes that this solution could help accelerate <img src="common/images/callcenteraibizview.png" align="center" width="535" height="479"/>
This is a sample accelerator for Call Center Intelligence powered by Azure AI (including new Azure OpenAI GPT-3). It shows how Azure AI services could be used both in real-time and post-call analytics scenarios for an Intelligent Contact Center.
This solution accelerator has two main components:
Real-time Intelligencecomponent: Real-time transcription and analysis of a call to improve the customer experience by providing insights and suggest actions to agents. This can help with agent-assist and virtual agents use cases. Key technical components of this part of the accelerator are:- Transcription of live audio stream using Azure Speech Service
- Entity extraction + PII detection and redaction using Azure Language Service
- Conversation summarization using Azure OpenAI Service
- Extract business insights & conversation details using Azure OpenAI Service
This is a web-based app that enables you to simulate Agent-Customer interactions (in any line of business) and shows the power of Azure AI to augment the human and acts as a very effective copilot (screenshot below) <img src="call-intelligence-realtime/common/images/sampleoutputaiintelligence-main.PNG" align="center"/>
To setup and run this solution component, please refer to Real-time Intelligence for step-by-step instructions.
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Post-call Analyticscomponent: Post-call analysis to create insights into customer conversations to improve understanding and support continuous improvement of call handling, optimization of quality assurance and compliance control as well as other insight driven optimizations. Key technical components of this part of the accelerator are:- Batch speech-to-text using Azure Speech: Transcribe large amounts of audio files asynchronously including speaker diarization and is typically used in post-call analytics scenarios. Diarization is the process of recognizing and separating speakers in mono channel audio data.
- Personally Identifiable Information (PII) extraction and redaction: Identify, categorize, and redact sensitive information in conversation transcription.
- Sentiment analysis and opinion mining: Analyze transcriptions and associate positive, neutral, or negative sentiment at the utterance and conversation-level.
- Visualize insights using Power BI
To setup and run this solution component, please refer to Post-call Analytics for step-by-step instructions.
This solution accelerator is modular and above two parts can be used independently of each other, if needed. i.e Real-time Intelligence and Post-call Analytics components can be used independently.
The diagram below depicts key components and Azure services used in this sample accelerator. <img src="common/images/highleveloverviewv2.png" align="center" width="564" height="385" />
Contents
Outline the file contents of the repository. It helps users navigate the codebase, build configuration and any related assets.
| Solution accelerator component | Folder | Description |
|---|---|---|
| Real-time Intelligence | call-intelligence-realtime | Web application & APIs that simulates real-time call intelligence. It performs real-time conversation transcription and extracts conversation information (including PII detection + redection). It also includes features to generate conversation summary using Azure OpenAI GPT-3 model along with ability to extract business insights in near real-time |
| Post-call Analytics | postcall-analytics-azure | ARM template file and deployment guide for performing ingestion & batch analytics of calls using various Azure AI services. This part of the accelerator can be to perform analytics on call recordings and does not require integration with telephony or other live-audio capturing mechanism. |
| Post-call Analytics | postcall-analytics-powerbi | Template files and deployment guide for visualizing call insights using Power BI. |
| (Optional) Real-time Intelligence or Post-call Analytics | azure-custom-speech | You could use standard Azure Sample data and instructions to create custom transcription model using Azure Speech service. This step produces a custom speech model. This step is OPTIONAL. |
Prerequisites
- An existing Azure Account
- Ensure you have Node.js installed. Required for
Real-time Intelligenceonly. - Ensure you have Power BI installed. Required for
Post-call Analyticsonly.
Dependencies
This accelerator is modular and some parts can be used independently and some components depend on other steps to be completed. In summary, real-time and post-call analytics can be used independently. Above table highlights key components of this solution.
Getting started
Follow the individual instructions for each step of the accelerator provided within above Folders.
License
Copyright (c) Microsoft Corporation
All rights reserved.
MIT License
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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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