AI-Powered Customer Support Hub
43% ticket deflection and 29% faster first response from a production-grade RAG chatbot.
About the client
B2B SaaS Platform (NDA)
United States
A fast-growing B2B SaaS company serving 2,000+ enterprise clients with a complex product suite. Their support team of 18 agents was being overwhelmed by a 40% YoY ticket volume increase, with response SLAs beginning to slip β jeopardising renewals for their highest-value accounts.
Technologies used
Results at a glance
43%
Ticket deflection rate
29%
Faster first response
4.6/5
Bot CSAT score
30 days
Time to production
The support team now handles 43% fewer tickets without any additional headcount. Agent satisfaction improved significantly β repetitive queries are handled automatically, leaving agents to focus on complex, high-value interactions.
Overview
The context
Enterprise SaaS companies face a brutal equation: product complexity drives high ticket volumes, but hiring support staff proportionally destroys unit economics. The answer is intelligent automation β but most chatbot implementations fail because they're bolted on as afterthoughts rather than built into the support workflow.
We designed this system from the ground up around the client's actual support data: 3 years of resolved tickets, their full product documentation, and their CRM. The result is a support experience that feels genuinely helpful β not like fighting a bot.
The challenge
The Challenge
The support team was spending 60% of their time answering the same 80 questions β product how-tos, billing queries, and integration setup. Agents had no tooling to quickly surface relevant docs or past resolved tickets, leading to long research times and inconsistent answers.
Previous chatbot attempts using off-the-shelf tools had failed: the bots gave confident but wrong answers, eroding customer trust. The team needed a solution that knew when to answer and when to escalate β and could do so with full context.
Our solution
What We Built
A production-grade RAG pipeline ingesting the client's full documentation, support history, and product changelog β updated nightly. The chatbot retrieves the most relevant context before generating answers, with citations so customers can verify information themselves.
When confidence is below threshold, the system routes to a live agent with a full conversation summary, the customer's account context from the CRM, and suggested responses β cutting agent ramp-up time per ticket from 4 minutes to under 45 seconds.
- RAG pipeline with nightly documentation sync
- Confidence-gated escalation to live agents
- CRM integration (HubSpot) for full account context
- Cited answers with source links
- Multi-channel: web widget, email, in-app
- Analytics dashboard with deflection and CSAT tracking
Outcomes
The results
The support team now handles 43% fewer tickets without any additional headcount. Agent satisfaction improved significantly β repetitive queries are handled automatically, leaving agents to focus on complex, high-value interactions.
43%
Ticket deflection rate
29%
Faster first response
4.6/5
Bot CSAT score
30 days
Time to production
βWe'd tried two chatbot vendors before. Both gave confident wrong answers. Chayaniq built something that actually understands our product β and knows when to hand off to a human.β
VP of Customer Success
B2B SaaS Company
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