AI BASED CUSTOMER SUPPORT CHATBOTS
Challenge
Businesses often struggle to provide instant, personalized, and accurate customer support, leading to delayed responses and lower customer satisfaction.
- Manual support teams are overburdened by repetitive queries, increasing operational costs.
- Inconsistent responses and limited availability reduce customer trust and engagement.
Approach
- Collect and analyze customer interaction data, including past chat logs, emails, and FAQs.
- Fine-tune a Gen AI language model to understand and respond to domain-specific queries.
- Define conversational workflows and intents to handle common questions, escalations, and personalized recommendations.
- Integrate the chatbot across web, mobile, and social media channels for multi-platform support.
Data
Depending on the business domain and data collected may use:
- Historical chat logs and support tickets
- Frequently asked questions (FAQs) and knowledge base articles
- Customer profiles and interaction history
- Product/service catalogs for reference and recommendations
Solution
- Context-aware responses that fetch customer, order, and item details from databases and external sources, supplemented with structured data such as JSON and CSV files.
- Retrieval-Augmented Generation (RAG) pipeline that enables the chatbot to answer questions using both database records and external documents.
- AI-powered response generation using OpenAI API and Mistral 7B language models to provide accurate, context-specific answers.
- Conversational flows that handle common queries, escalations, and personalized recommendations.
- Monitoring dashboards and logging tools that track chatbot interactions and continuously update the knowledge base for improved performance.
Business Impact
- Faster resolution of customer queries, reducing wait times and improving satisfaction.
- Reduced operational costs through automation of repetitive support tasks.
- Enhanced customer engagement and loyalty via consistent, personalized interactions.
- Scalable support that handles higher volumes without additional staff.
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