Deskwise AI

Brightline Apparel's support team was growing faster than its headcount could keep up with. As order volume tripled year over year, so did the ticket queue — shipping questions, return requests, and promo code errors piled up across email, live chat, and social DMs, with no single view of what needed attention first.

Response times stretched past 24 hours during peak periods, and the team's five agents were spending most of their day answering the same handful of questions instead of handling the complex, high-value conversations that actually needed a human. First-response time had climbed to nearly nine hours, and CSAT scores were sliding as customers waited longer for answers that, in many cases, already existed somewhere in the help center. Leadership needed a way to triage and resolve routine tickets automatically without sacrificing the quality or tone customers expected from the brand.

Existing helpdesk tools offered canned responses and basic routing rules, but nothing that actually understood ticket content, pulled from the knowledge base intelligently, or learned from how the team's best agents actually replied. Brightline needed a system that could read a ticket the way a trained agent would — and act on it.

Within the first full quarter after launch, Deskwise AI was resolving nearly half of Brightline Apparel's incoming ticket volume without any agent involvement, and cut average resolution time by 41% across the board. First-response time dropped from hours to just over two minutes on AI-handled conversations, and CSAT climbed three points as customers got faster, more consistent answers.

We're continuing to expand Deskwise AI's language coverage and add outbound proactive notifications (like shipping delay alerts) so fewer tickets get created in the first place — shifting the model from reactive deflection to genuine issue prevention.