Enhancing Logistics Operations with an AI Assistant for a Mid-Size U.S. Company
Developed and deployed a GenAI-powered customer support assistant for a mid-size U.S.-based automotive equipment manufacturer. The solution aimed to streamline customer support operations, improve query handling, and enhance user experience. Integrated with HubSpot CRM, the AI assistant automated ticket creation, order tracking, sentiment analysis, and smart escalation. The project resulted in improved self-service rates, reduced operational costs, and enhanced CSAT scores.
What was the main challenge in this project?
>> High support costs (~$0.9M/year) due to large teams working in shifts.
>> Rule-based assistant limitations and inability to understand user intent.
>> Scattered documentation and lack of intelligent query prioritization.
>> High false escalations and long troubleshooting times.
What was your solution or approach?
>> Built a GenAI-powered support assistant integrated with HubSpot CRM.
>> Implemented a hybrid model using GPT-4, Langchain, and Pinecone for natural language understanding and document retrieval.
>> Deployed in stages: first as an internal support copilot for agents, then as a customer-facing assistant.
>> Integrated features like smart ticket routing, sentiment analysis, real-time order tracking, and cross-sell recommendations.
What was the outcome or impact for the client?
>> Self-service increased from 15% to 55%, auto-resolving ~2,800 issues/month.
>> Reduced false escalations from 50% to 11% (78% reduction).
>> Average troubleshooting time reduced by 58% (from 15 mins to 6 mins 20s).
>> Annual support spend dropped by $245K.
>> CSAT score improved from 82 to 91 (+9 points).
>> Net incremental revenue from AI-driven offers reached $1.25M/year.