Case studyAI Automation

BookieLink Customer Support Bot

A RAG-powered support bot trained on thousands of BookieLink Q&A records. It handles repetitive customer questions automatically, reduces support tickets, and frees the team for higher-value cases.

System stack
n8n
OpenAI API
Vector Database
Webhooks
Built forA real operational bottleneck
Business impactA faster, more reliable workflow
Delivery approachScoped, built, tested, and documented
01

Client challenge

BookieLink's support volume exceeded what their small team could manage. Repetitive questions were consuming hours daily, delaying responses to complex cases that genuinely required human attention.

02

What I built

I built a RAG-powered support chatbot trained on 5,000+ Q&A pairs covering BookieLink's full product surface — deployed as a front-line agent capable of handling the majority of incoming queries autonomously.

  • 5,000+ Q&A dataset for RAG training
  • Vector-based semantic similarity search
  • Automatic escalation for unrecognized queries
  • Webhook-based deployment and session management
  • OpenAI-powered natural language response layer
03

Measured outcomes

The bot achieves 85% query accuracy and reduced support tickets by 70% in the first month. The team now handles only complex escalations — recovering hours of daily capacity that were previously consumed by repetitive queries.

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4 project views
BookieLink support assistant interface — view 1

Primary workflow view

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