The Challenge
A B2B SaaS platform was scaling faster than their support team could hire. Response times were increasing, customer satisfaction was dropping, and the team was burning out on repetitive questions that had clear answers in their documentation.
The Solution
We built a RAG-powered AI support agent trained on their documentation, knowledge base, and historical support tickets. The agent handles first-line support, escalates complex issues to humans, and continuously learns from resolved tickets.
Key Features
- Natural language understanding with context from the full conversation history
- RAG pipeline indexing 500+ documentation pages and 10K+ resolved tickets
- Intelligent escalation with full context handoff to human agents
- Multi-channel deployment (in-app widget, email, Slack)
- Analytics dashboard tracking resolution rates and common topics
The Results
- 70% of inquiries resolved without human intervention
- Average response time reduced from 4 hours to under 30 seconds
- Customer satisfaction increased from 3.2 to 4.6 (out of 5)
- Support team refocused on complex, high-value interactions
Technology Stack
Claude API, Weaviate vector database, Next.js, Supabase, custom RAG pipeline