CUSTOMER SUPPORT & AGENTIC AI

Autonomous Multi-Agent Customer Support Crew

Deploying AutoGen support agent crews to read Zendesk tickets, query vector knowledge bases, and execute backend refunds and tier upgrades autonomously.

Architect: Rohit • Key Impact: 74% Auto-Resolution Rate (2.4 Min Avg Time)

Client & Enterprise Challenge

Customer support queues averaged 18-hour response times during product launches, causing customer churn and overwhelming human support staff.

AutoGenZendesk APIPineconeFastAPIPythonOAuth

The Technical Solution & Architecture

Rohit built an autonomous multi-agent support crew integrated with Zendesk webhooks. The agents classify ticket intent, query Pinecone vector knowledge bases, and execute authorized backend actions autonomously.

Verified Quantifiable Business Metrics

74% Auto-Resolution

Resolved 74% of incoming tier-1 technical support tickets with zero human intervention.

2.4-Minute Resolution Time

Slashed average ticket resolution duration from 18 hours down to 2.4 minutes.

96% Customer CSAT

Maintained exceptional customer satisfaction scores across automated interactions.

Executive Client Review

"Rohit's Zendesk support agent crew reduced our ticket queue backlog instantly. Customers get accurate answers in minutes, and our human agents can focus on VIP accounts."

— Executive Leadership Team, High-Volume Global SaaS Enterprise

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Lead Architect

Rohit - AI Consultant

Rohit

AI & Data Science Consultant

2+ Decades AI Experience

Building neural networks since 2004 at IIT Roorkee (mentored by Dr. Sunil Padhi, HOD Electrical Dept) and Unix CDR automation scripts at Xalted Bengaluru in 2007 (mentored by Srinivas Sir). Specializing in Agentic AI, Enterprise RAG, and MLOps.

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