The Challenge
SaaS platforms with large customer bases typically face a situation where support teams handle thousands of tickets per day — 70–80% of which are the same 30–40 questions repeated over and over. Average first response time runs 4–8 hours, CSAT scores suffer, and hiring more agents is economically unsustainable.
Our Solution
We build LLM-powered support bots with a RAG pipeline over your entire documentation, knowledge base, and resolved ticket history — capable of understanding natural language questions, looking up account-specific data, and resolving issues end-to-end without human intervention.
What We Built
- Process and embed documentation pages, resolved tickets, and SOPs into a vector database for accurate retrieval
- Build a multi-step reasoning agent that can query CRMs, check account status, reset features, and trigger actions — not just answer questions
- Integrate across Intercom, email, and in-app help widgets simultaneously with a single deployment
- Build human escalation flows that transfer full context so agents never ask customers to repeat themselves
- Create analytics dashboards tracking resolution rate, escalation reasons, and satisfaction by query category
Results: Before vs After
| Metric | Before | After | Change |
|---|---|---|---|
| Tickets handled by AI | 0% automated | 80–90% automated | ↑ 80+ pts |
| First response time | 4–8 hours | < 2 seconds | ↓ 99.9% |
| Support cost per ticket | High (human agent) | Fraction of original | ↓ 85–95% |
| CSAT score | Typically 3.0–3.5/5 | 4.5+/5 achievable | ↑ 40–50% |
| Payback period | — | Typically 4–8 weeks | Fast ROI |
Timeline
Typically 6 weeks to full production deployment
Technologies
“The right AI support bot eliminates repetitive ticket load, gives customers instant answers, and lets your human agents focus exclusively on the complex problems that actually need human judgement.”
What this means for your support team
Could this be your business?
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