SaaS · Customer Support

💬 AI Chatbots & Agents

Custom AI Support Agent Cuts Ticket Volume by 70% for Global SaaS Company

A RAG-powered AI agent trained on product documentation and support history resolves 70% of tickets automatically — 24/7, zero additional headcount.

70%

Reduction in tickets reaching human agents

24/7

Support coverage with zero out-of-hours cost

1.4s

Average AI response time vs 4-hour SLA

Patient data sent to public AI — private RAG only

— The Situation

The challenge and the solution

// The Challenge

A growing SaaS company with a global customer base and a support team stretched across time zones.

A B2B SaaS company with customers across the US, UK, and Australia was struggling with support volume. Their 6-person support team was fielding 1,800 tickets per month — 70% of which were repeat questions about features, pricing, onboarding, and integration guidance that were all already answered in the product documentation.

1,800 tickets per month — 70% repeat queries already answered in documentation
Support team spending 60% of time on routine questions, 40% on complex issues
No out-of-hours coverage — US and Australian customers waiting hours for simple answers
4-hour average first response SLA difficult to maintain at peak volume
Hiring more support staff not viable — would double the support cost for routine queries

// The Solution

A private RAG-powered AI agent trained on their documentation and support history — live in 6 weeks.

We built a custom AI support agent using RAG architecture — trained on the company's product documentation, historical support tickets, and knowledge base. Deployed as a widget in the customer portal and integrated with Zoho Desk. All processing runs inside the company's Azure environment — no customer data touches public AI APIs.

RAG pipeline built on product docs, support history, feature guides, and integration documentation
Deployed as an in-portal chat widget and email response assistant simultaneously
Zoho Desk integration — AI resolves routine queries, creates tickets for complex ones with context pre-filled
Confidence threshold: below 85%, agent escalates to human with full conversation context
All processing inside Azure private endpoint — zero data egress to public APIs

— What We Built

Six components of the solution

Every piece designed to solve a specific part of the problem — integrated into one system that works end-to-end.

📚

Multi-Source RAG Knowledge Base

Indexed 1,240 documentation pages, 18 months of resolved tickets, feature guides, and integration docs. Updated automatically when documentation is revised.

🔒

Private Azure Deployment

All LLM inference runs inside the company's Azure OpenAI private endpoint. Customer queries never reach a public API. Full GDPR compliance maintained.

🎧

Zoho Desk Integration

AI responses surfaced directly in Zoho Desk as suggested replies. Tickets below confidence threshold auto-created with full conversation history for human agents.

🌐

In-Portal Chat Widget

Customer-facing chat widget embedded in the product portal. Authenticated against customer account — AI sees the customer's plan, usage, and open tickets before responding.

📊

Knowledge Gap Dashboard

Tracks queries that AI couldn't answer confidently. Product and support teams use it to fill documentation gaps — agent quality improves continuously.

⚡

Intelligent Escalation

When AI detects frustration signals, billing disputes, or complex technical issues — it escalates immediately to a human agent with the full conversation context pre-loaded.

— Results

What this delivered for the client

The numbers — measured outcomes

70%

Ticket volume reduction — 1,260 of 1,800 monthly tickets now resolved by AI without human involvement

1.4s

Average AI response time — vs 4-hour human SLA the company was struggling to maintain

24/7

Support coverage achieved with zero additional staffing cost for out-of-hours queries

87%

Customer satisfaction score on AI-handled interactions — above the previous human-only baseline of 81%

✓

Support team refocused on high-value work

With 70% of routine tickets handled by AI, the 6-person support team refocused entirely on complex technical issues, enterprise account management, and proactive customer success. Morale improved measurably.

✓

Australian and US time zones fully covered

Previously, customers in Australia waited until the UK team came online. Now, routine queries are resolved instantly regardless of time zone — a significant competitive improvement.

✓

AI customer satisfaction exceeded human baseline

Counterintuitively, customers rated AI-handled interactions at 87% satisfaction — above the previous human-only score of 81%. Speed of response was the primary driver.

"Quite possibly the best programming team on the planet. Went WAY above and beyond without charging more. The AI agent they built has completely transformed how we handle support."

Chris

SaaS Platform · United States

— Delivery Timeline

How we delivered it

From the initial audit to live deployment — every stage designed to minimise risk and maximise speed to value.

Week 1–2

📚

Knowledge Base Preparation

Indexed all documentation, cleaned 18 months of historical tickets, identified top 50 query categories. Data quality check — removed outdated content that would cause incorrect answers.

Week 3–4

🔒

RAG Pipeline & Private Deployment

RAG pipeline built and deployed to Azure private endpoint. Prompt engineering for response quality and escalation detection. Confidence scoring calibrated against historical query set.

Week 5

🔗

Zoho Desk & Portal Integration

Chat widget integrated into product portal. Zoho Desk connection built — AI responses as suggested replies, auto-ticket creation on escalation. Two-week parallel run begins.

Week 6–7

🚀

Go-Live & Optimisation

Full deployment. Knowledge gap monitoring dashboard live. First optimisation cycle at day 14 based on unresolved query patterns. Ticket volume reduction visible within 72 hours of launch.

— Technology stack

Azure OpenAI (Private)LangChain · RAG PipelinePinecone Vector DBZoho Desk APIReact WidgetPython · FastAPI