Chatbot Solution using Azure Cognitive Services: 6-week PoC

One of the biggest challenges faced by businesses in customer-centric industries such as e-commerce, financial services, healthcare, travel and tourism, customer service, etc. is to handle a large volume of customer inquiries efficiently. Manual handling of customer inquiries can be time-consuming, and error-prone and result in a delay in response time, leading to a negative impact on the customer experience. Additionally, businesses may struggle to identify prospective sales leads from customer inquiries.

Affine's chatbot solution is designed to address these challenges by leveraging Azure Cognitive Services to accurately identify the intent and entities of customer queries, enabling the chatbot to classify them into prospective sales leads. The solution can be easily trained using FAQ data, enabling businesses to quickly get up and running with minimal setup time.

The MVP solution utilizes various Azure services such as Azure ML, Bot Service, App Service, QnA Maker, Language Understanding, and Cosmos DB to create a robust and efficient chatbot.

This Proof-of-Concept implementation can be expanded to your production environment.

Benefits:

• Improved Customer Experience - The chatbot provides quick and accurate responses to customer inquiries, leading to an improved customer experience.
• Improved Efficiency and Reduced Workload - The chatbot reduces the workload of customer service teams, resulting in cost savings for the business.
• 24/7 Availability - The chatbot is available 24/7, enabling customers to receive support at any time of the day, improving customer satisfaction.

Agenda (6 weeks):

• Business & Data Understanding: Gain a holistic understanding of the business requirements and define the scope, including identifying the types of inquiries as specific or non-specific.
• FAQ Creation: Create a knowledge base in collaboration with stakeholders by ingesting and pre-processing data and adding metadata tags for QnA.
• Classification Model Development: Develop an NLP engine to identify specific and non-specific inquiries and validate the model through testing.
• Chatbot Creation: Leverage Azure services such as Azure Bot Services, LUIS, and QnA Maker to develop the chatbot, and perform internal testing and validation of the framework.
• User Interface: Design and develop a user-friendly chatbot interface and conduct thorough testing to ensure an optimal user experience.
• Data Storage: Create a data storage layer to store conversations, feedback, and logs securely.
• Deployment: Deploy the chatbot for UAT testing on the client's internal infrastructure.
• UAT Testing: Engage key stakeholders from the client to perform UAT testing and collect feedback from key business stakeholders to improve the chatbot's performance.

Why Affine

Enabling business-focused data science, AI, and BI development with deep domain expertise. 

Affine believes in faster design to faster deployment through key differentiators- Experimentation Focus and Speed to Value.