Generative AI: Customer Support Automation
A business receives hundreds of invoices daily, which are manually processed. By using Azure Form Recognizer (a service in Azure Cognitive Services), the company automates the extraction of key details such as vendor names, invoice numbers, amounts, and dates from PDFs or images. The extracted data is then passed through an Azure Logic App to automatically update the accounting system via an API integration with their ERP. Additionally, Azure Monitor tracks processing performance, and any inconsistencies are flagged by an integrated Azure Machine Learning model for further review. This solution improves speed, accuracy, and scalability of invoice handling while reducing manual labor.
Identify Use Cases and
Business Objectives
Define key customer support tasks for automation, such as handling FAQs, troubleshooting issues, or processing customer orders. Align the chatbot's objectives with business goals like reducing response times, improving customer satisfaction, or cutting support costs.
Develop and Train Chatbot with AI
Use Azure Bot Service integrated with Cognitive Services (e.g., Language Understanding - LUIS) to create a chatbot capable of understanding natural language queries. Train the bot using historical support data and FAQs, and fine-tune it to handle complex, multi-turn conversations with human-like responses.
Deploy, Monitor, and Continuously Improve
Deploy the chatbot across multiple channels (web, mobile, social media) using Azure Bot Framework. Integrate with Azure Monitor for real-time performance tracking and use feedback loops to retrain and improve the bot's accuracy and ability to handle more complex queries over time.
