QA relied on fractional manual checks. AI now analyzes every conversation to drive specific coaching plans.
A fintech serving 2 million members that has provided more than $16.6 billion in responsible credit since inception.
The organization relied on resource-intensive manual sampling for quality assurance, leaving most interaction data untapped and creating blind spots...
“We were completely inefficient.”
Fintech platform for personal loans and automated savings tools.
Generative AI platform for contact center automation and agent productivity.
Oportun's Quality assurance is part of this use case:
Related implementations across industries and use cases
Vague surveys hid why 360K members called. Managers now use AI to analyze every conversation, score agents, and train support chatbots.
Rising volume buried agents in manual tasks. AI now fields routine chats and writes summaries, cutting wrap-up time in half.
Tools failed on Hindi-English mixes, limiting QA to <10% of calls. AI now transcribes every word to audit 100% of interactions.
Vague surveys hid why 360K members called. Managers now use AI to analyze every conversation, score agents, and train support chatbots.
Manual QA left 90% of calls unchecked. AI now audits every interaction, accurately capturing mixed Hindi-English conversations.
Minor compliance updates once forced full video reshoots. Now, course creators generate and edit AI avatar videos directly from text.
Shifting to B2B sales exposed disconnected workflows and anecdotal forecasts. Now, AI analyzes interactions to surface deal intelligence.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.
Sourcing native speakers for 14 markets was costly. Now, AI handles 40% of routine queries and translates live for a central English team.
QA relied on fractional manual checks. AI now analyzes every conversation to drive specific coaching plans.
A fintech serving 2 million members that has provided more than $16.6 billion in responsible credit since inception.
The organization relied on resource-intensive manual sampling for quality assurance, leaving most interaction data untapped and creating blind spots...
“We were completely inefficient.”
Fintech platform for personal loans and automated savings tools.
Generative AI platform for contact center automation and agent productivity.
Oportun's Quality assurance is part of this use case:
Related implementations across industries and use cases
Vague surveys hid why 360K members called. Managers now use AI to analyze every conversation, score agents, and train support chatbots.
Rising volume buried agents in manual tasks. AI now fields routine chats and writes summaries, cutting wrap-up time in half.
Tools failed on Hindi-English mixes, limiting QA to <10% of calls. AI now transcribes every word to audit 100% of interactions.
Vague surveys hid why 360K members called. Managers now use AI to analyze every conversation, score agents, and train support chatbots.
Manual QA left 90% of calls unchecked. AI now audits every interaction, accurately capturing mixed Hindi-English conversations.
Minor compliance updates once forced full video reshoots. Now, course creators generate and edit AI avatar videos directly from text.
Shifting to B2B sales exposed disconnected workflows and anecdotal forecasts. Now, AI analyzes interactions to surface deal intelligence.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.
Sourcing native speakers for 14 markets was costly. Now, AI handles 40% of routine queries and translates live for a central English team.