AI Customer Support

How we built an AI chatbot for customer support.

Industry

E-Commerce

Timeline

3 months

Status

Completed

The Problem

Customer support team overwhelmed with 10,000+ daily inquiries.

Overview

An e-commerce company was struggling with customer support scalability, receiving over 10,000 daily inquiries. We implemented an AI-powered chatbot solution using LLMs that dramatically reduced response times and improved customer satisfaction.

The Challenge

The support team was unable to handle the volume of inquiries, leading to long wait times and customer frustration. Many common questions were repetitive and could be automated. The company needed a solution that could handle multiple languages and complex product-related queries.

Our Solution

We built an LLM-powered chatbot using OpenAI's API, LangChain for orchestration, and a custom knowledge base integrated with their product database. The frontend was built with React for seamless integration into their website. Python backend handled API orchestration and logging.

Implementation

Phase 1 involved training the model with historical support tickets and product documentation. Phase 2 focused on integration with their CRM and knowledge management systems. Phase 3 included gradual rollout with human escalation for complex issues. Continuous monitoring and fine-tuning improved accuracy over time.

Our Approach

Implemented LLM-powered chatbot with knowledge base integration.

Technology Stack

OpenAILangChainReactPython

Results

The chatbot resolved 70% of queries without human intervention, provided 24/7 availability, and reduced support costs by 40%. Average response time dropped from 4 hours to instant, significantly improving customer satisfaction scores.

Key Outcomes

70% query resolution

24/7 availability

40% cost reduction

Key Learnings

1

LLMs require quality training data and continuous refinement

2

Human escalation paths are essential for complex issues

3

Integration with existing systems is critical for success

4

User feedback loops improve chatbot accuracy significantly

5

Transparency about AI limitations builds customer trust

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