SupportBot AI_
An AI-powered customer support chatbot handling common inquiries with OpenAI integration, knowledge base retrieval, and intelligent ticket escalation for 24/7 support.
Entity_Client
HelpDesk Pro
Primary_Role
AI Integration
Duration_Log
6 weeks
Resource_Team
2 developers
Project_Overview
HelpDesk Pro's support team was overwhelmed with 300+ tickets daily, causing 24-hour response times. Many were repetitive questions about billing, refunds, and password resets. They needed an AI chatbot to handle routine inquiries and escalate complex issues to humans.
Operational_Process
Built context-aware chatbot using OpenAI's API with retrieval-augmented generation (RAG) from internal knowledge base. Implemented confidence scoring for escalation and integrated with existing ticketing system.
Core_Capabilities
Performance_Metrics
Support Tickets
DATA_POINT: human handled
Response Time
DATA_POINT: average
Response Accuracy
DATA_POINT: reliability
Team Capacity
DATA_POINT: without hiring
Satisfaction Score
DATA_POINT: out of 5
Labor Savings
DATA_POINT: first year
Conflict_Resolution
Implemented retrieval-augmented generation (RAG) using vectorized knowledge base, added confidence scoring, and created guardrails to refuse questions outside scope. Accuracy improved to 97% with 0.2% hallucinations.
Implemented conversation memory using Redis, maintained context window, and structured prompts to reference previous messages. Context retention improved to 99.5%.
Improved prompt engineering, added follow-up question capabilities, expanded knowledge base, and adjusted confidence thresholds. Escalation rate reduced to 22%.
Optimized prompts, implemented request caching, used cheaper GPT-3.5 for simple queries with GPT-4 for complex ones, and added rate limiting. Cost per conversation reduced to $0.08.