Automated Call Summaries
Convert customer calls into organized, actionable summaries that help managers understand interactions without relying solely on manual review or limited sampling.
Turn customer conversations into clear, actionable insights with EmberQA AI Call Summaries. Analyze interactions, surface sentiment and red flags, search transcripts, and connect findings to coaching and quality workflows. Built for contact centers and customer-facing teams across the United States, EmberQA helps managers move beyond limited manual sampling and make better decisions with comprehensive interaction data.
Transform customer interactions into searchable summaries, quality insights, risk signals, and coaching opportunities.
Convert customer calls into organized, actionable summaries that help managers understand interactions without relying solely on manual review or limited sampling.
Analyze calls and other customer interactions with customizable rubrics, sentiment analysis, and AI scoring designed to create more consistent QA visibility.
Surface hostile behavior, privacy violations, escalation risks, and other configurable concerns so teams can identify urgent quality issues more efficiently.
EmberQA helps contact centers and customer-facing teams make more of every conversation by combining AI-generated call summaries with automated scoring, sentiment analysis, transcript search, and configurable red flags. Instead of relying only on limited manual sampling, managers can gain broader visibility into interaction quality, identify recurring patterns, and connect findings to focused coaching and workflow actions across their operations.
EmberQA connects comprehensive interaction analysis with practical quality improvement workflows.
Evaluate more customer interactions without adding the same manual review burden for managers.
Apply custom rubrics and quality standards consistently across calls, SMS, emails, and documents.
Use recurring performance patterns to guide more focused, personalized agent coaching conversations.
Configure red flags that help teams identify privacy, conduct, and escalation concerns sooner.
AI automation and contact-center software experience power EmberQA's platform.
CEO / Founder
RT Maddox is the CEO and Founder of EmberQA, an AI-powered quality assurance platform built for contact centers and customer-facing teams across the United States. With a background in AI automation and contact-center software, RT identified a critical gap between the volume of customer interactions companies handle and the limited manual sampling traditionally used to evaluate them. Drawing on years of hands-on collaboration with customer-obsessed organizations, RT led the development of EmberQA to bring automated scoring, red flag detection, and targeted coaching insights to a broader range of businesses. As founder, RT is focused on helping quality assurance teams move beyond guesswork, giving managers the tools to review every interaction and turn QA data into measurable performance improvement for their agents and their customers.
Head of Engineering
Ethan Shover serves as Head of Engineering at EmberQA, where he leads the technical development of the company's AI-powered quality assurance platform. Ethan is responsible for building the systems that allow EmberQA to analyze every customer interaction, apply consistent scoring rubrics, and surface urgent red flag alerts in real time. His engineering leadership ensures that the platform can reliably support office-specific QA workflows and integrate customer call data with CRM verification, giving quality assurance teams and contact centers a scalable, dependable tool for improving performance. Ethan brings a strong focus on building robust, high-performing software that translates complex AI automation into practical, actionable insights for organizations managing high volumes of customer interactions. His work is central to EmberQA's mission of transforming manual QA sampling into comprehensive, data-driven interaction analysis.
A call summary is a concise account of a customer conversation that captures important topics, outcomes, concerns, and follow-up needs. AI call summaries help teams understand interactions without reviewing every recording from beginning to end. When combined with EmberQA's scoring, sentiment analysis, red flag detection, and transcript search, summaries can support more efficient quality assurance and more focused coaching.
Talk with EmberQA about turning interaction data into practical QA insights.
Connect with EmberQA to discuss AI call summaries, quality assurance, and interaction analysis for your organization.
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