Vague surveys hid why 360K members called. Managers now use AI to analyze every conversation, score agents, and train support chatbots.
A top 100 U.S. credit union managing nearly $6 billion in assets and serving 360,000 members.
Traditional post-interaction surveys failed to provide the granular insights needed to understand why members were calling or what influenced their...
“Capacity is our first stop to understand not only what our members are saying but what’s driving those comments and what we can do to improve that and get ahead of the curve.”
Credit union offering banking, loan, and investment services for members.
AI-powered support automation platform for customer and employee helpdesk tasks.
BCU's Quality assurance is part of this use case:
Related implementations across industries and use cases
Agents toggled 15 systems while a rigid bot escalated 26% of chats. AI now resolves routine cases, cutting escalations by 15%.
Student insights were trapped in unreviewed audio. AI securely evaluates every call to power instant feedback and proactive coaching.
Agents typed furiously while customers waited on hold. AI now summarizes calls, saving the team 250,000 hours annually.
Student insights were trapped in unreviewed audio. AI securely evaluates every call to power instant feedback and proactive coaching.
Analysts audited 3% of 70k monthly tickets. AI now evaluates every interaction, reopening predicted negative cases for human agents.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.
Vague surveys hid why 360K members called. Managers now use AI to analyze every conversation, score agents, and train support chatbots.
A top 100 U.S. credit union managing nearly $6 billion in assets and serving 360,000 members.
Traditional post-interaction surveys failed to provide the granular insights needed to understand why members were calling or what influenced their...
“Capacity is our first stop to understand not only what our members are saying but what’s driving those comments and what we can do to improve that and get ahead of the curve.”
Credit union offering banking, loan, and investment services for members.
AI-powered support automation platform for customer and employee helpdesk tasks.
BCU's Quality assurance is part of this use case:
Related implementations across industries and use cases
Agents toggled 15 systems while a rigid bot escalated 26% of chats. AI now resolves routine cases, cutting escalations by 15%.
Student insights were trapped in unreviewed audio. AI securely evaluates every call to power instant feedback and proactive coaching.
Agents typed furiously while customers waited on hold. AI now summarizes calls, saving the team 250,000 hours annually.
Student insights were trapped in unreviewed audio. AI securely evaluates every call to power instant feedback and proactive coaching.
Analysts audited 3% of 70k monthly tickets. AI now evaluates every interaction, reopening predicted negative cases for human agents.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.