NexBridge Support Intelligence
A support chatbot that answers the routine questions on its own and hands the hard ones to a human, fully briefed.
The Challenge
The NexBridge support team was handling around 800 tickets a month, and roughly 60 percent were questions the documentation already answered. Agents spent their days repeating the same information instead of solving the genuinely hard problems. During busy periods, first responses slowed down, and in financial data, slow support costs trust. They needed to absorb the routine volume without hiring.
The NexBridge support team was handling around 800 tickets a month, and roughly 60 percent were questions the documentation already answered.
Overview
NexBridge provides financial data services to customers who expect quick, precise support. Their team was swamped by questions that already had documented answers, while the complex cases waited in the same queue. They asked us to take the routine volume off their agents without taking humans out of the loop. We built the system to fit into their existing Salesforce workflow rather than replace it.
Retrieval-Augmented Answers
Instead of inventing answers, the chatbot looks them up. Every question triggers a search over the indexed product documentation, and the closest-matching passages shape the response. When the documentation changes, the index updates with it, so answers never drift out of date. The bot can only say what the docs support, which is exactly the point.
Grounding and Citations
Every answer includes a link to the documentation section it came from. Customers can click through to confirm a detail or read more. That transparency builds trust, and it makes any wrong answer easy to trace and fix at the source. Better documentation improves the bot, and the bot shows exactly where the documentation needs work.
Salesforce Escalation
When the chatbot can't answer confidently, or a customer simply wants a person, it opens a Salesforce case on the spot. The case arrives with the full conversation and the relevant documentation already attached. Agents skip the usual opening round of questions and get straight to solving. Cleaner tickets, faster resolutions.
Measurement
We instrumented everything from day one: deflection, response times, satisfaction scores. The dashboards show NexBridge exactly which question types the bot handles well and where it stumbles. When gaps appear, the documentation team knows precisely what to write next. The system keeps improving instead of plateauing after launch.
Results
Within its first months live, the chatbot resolved well over half of all incoming questions. First responses on the remaining tickets sped up by 40 percent as agents shed the routine load. Customers rated their conversations 4.6 out of 5. NexBridge absorbed its full support volume without adding a single hire.
Outcomes and Metrics
The chatbot now handles most of the repetitive questions on its own. First responses got faster because agents are no longer buried under routine tickets. The cases that do reach a human arrive with context, so they get resolved sooner too. Customers rated the experience 4.6 out of 5, which tells us the answers are not just fast but right.
58%
Ticket Deflection
Incoming questions the chatbot resolves on its own, no agent needed.
40%
First-Response Time
Faster first responses on the tickets that still reach a human.
4.6/5
User Satisfaction
Average rating customers gave their conversations with the chatbot.
100%
Answer Sourcing
Answers that link back to the exact documentation they came from.
Engagement Process
Every Devyst engagement follows a structured process: discovery, architecture, build, and handoff. This project was no different. We aligned on scope, reviewed existing systems, delivered iteratively, and handed off with documentation and runbooks.