The Problem

A B2C cybersecurity SaaS company with a 30–50 person team was receiving a growing number of support requests across FAQs, product issues, account questions, security concerns, and urgent incidents.

As volume increased, the support team had to manually review repetitive queries while also identifying which issues needed immediate escalation.

This created operational drag:

• Repetitive FAQs consumed support bandwidth.

• Urgent issues were mixed with routine requests.

• Escalation depended on manual review.

• Critical incidents could be delayed outside working hours.

• CSAT feedback and support insights were not captured consistently.

The company needed faster first response, cleaner issue triage, and a more reliable escalation workflow.

The Solution

Zuvtor developed an AI Customer Support Assistant to act as the first layer of support.

The assistant instantly answered common questions, guided customers through product issues, classified severity, escalated unresolved cases, and alerted the team when critical incidents appeared.

It was designed to support the team, not replace it, by handling routine support while routing complex or urgent cases to humans.

What Was Built

Conversation Layer

The AI assistant was trained to handle customer conversations in a clear and support-friendly tone.

It could:

• Answer FAQs instantly

• Respond to common product issues

• Ask follow-up questions to understand the issue

• Classify severity as Urgent, High, or Low

• Let customers know when human support was needed

• Capture CSAT feedback after the interaction

This gave customers immediate help without requiring human review for every basic query.

Automation Layer

Behind the conversation, the assistant triggered support actions based on the customer’s issue.

It could:

• Escalate unresolved cases automatically

• Create tickets in Zendesk

• Send email alerts for critical incidents

• Capture CSAT feedback

• Store support data for analytics and reporting

This made the support flow more controlled and reduced the chance of urgent issues being missed.

Tech Stack / Integration Layer

The solution connected the customer-facing assistant with the company’s support and alerting workflow.

Core tools and integrations included:

• Botpress for the AI support assistant and conversation flow

• Make.com for automation logic, routing, and workflow orchestration

• Zendesk for ticket creation and escalation tracking

• Email alerts for critical incidents

• CSAT and analytics layer for feedback, severity trends, and support visibility

Every important interaction was either resolved, escalated, or tracked.

What This Solution Enables

The AI Customer Support Assistant gave the company a faster and more reliable first-response layer.

It helped the team:

• Reduce repetitive FAQ handling

• Improve first response time

• Separate urgent issues from routine requests

• Escalate critical incidents faster

• Create support tickets without manual copying

• Capture customer feedback more consistently

• Improve visibility into recurring issues and support quality

• Provide support coverage outside working hours

The biggest value was not just faster replies. It was better control over the support flow.

Customers received immediate help, while the support team gained a clearer system for triage, escalation, and follow-up.

Want to see how this could work for your firm? Book a discovery call.