CASE STUDY: B2B SAAS

Achieving 70% Auto-Resolution Rate with AI Support Agents

How a B2B platform with 12,000 enterprise users reduced support escalations by deploying context-aware AI agents.

70%
Auto-Resolution
$180k
Annual Savings
4.8★
CSAT Score
2min
Avg Resolution

The Problem

The client's support team was drowning in repetitive technical questions. With 3,000+ tickets monthly, senior engineers were spending 60% of their time on L1 issues instead of product development.

  • API integration questions consuming engineering hours.
  • Inconsistent responses across different support agents.
  • Long wait times driving enterprise churn risk.

The Architecture

We built a RAG-Enhanced Support Agent with direct access to their documentation and codebase.

Technical Components:

  • RAG Pipeline Pinecone vector DB indexing 500+ docs, API specs, and changelogs.
  • Code Context Agent Pulls relevant code snippets from GitHub to answer integration questions.
  • Escalation Guard Confidence scoring to route complex issues to humans instantly.

The Results

After 60 days, the AI agent handled 70% of all technical inquiries without human intervention. Engineers reclaimed 25+ hours/week. The client avoided hiring 2 additional support staff, saving $180k/year.