AI Interaction Scoring
EmberQA uses AI to score customer interactions across calls, SMS, emails, and documents with customizable quality assurance scorecards and rubrics.
EmberQA helps U.S. contact centers and customer-facing teams automate quality assurance across calls, SMS, emails, and documents. AI scores every interaction, identifies red flags, analyzes sentiment, and recommends focused coaching, giving managers clearer performance visibility without relying on limited manual sampling. Turn scattered QA data into practical insights, consistent evaluation, and measurable improvement for agents and customers.
Automate interaction analysis, quality scoring, risk detection, coaching, and workflow actions across customer service operations.
EmberQA uses AI to score customer interactions across calls, SMS, emails, and documents with customizable quality assurance scorecards and rubrics.
Identify hostile behavior, privacy violations, escalation risks, and other urgent quality concerns through customizable AI alerts and interaction analysis.
Use performance patterns to recommend personalized coaching and support AI roleplay training scenarios that help agents develop practical customer service skills.
EmberQA helps U.S. contact centers move beyond limited manual sampling by analyzing every customer interaction across supported channels. Custom scorecards, sentiment analysis, searchable transcripts, red flag detection, and performance analytics help managers find meaningful patterns faster. Workflow automations can trigger actions in CRMs and ticketing systems, while targeted coaching recommendations connect QA findings to measurable performance improvement.
Built to help customer-facing teams replace scattered QA data with actionable performance intelligence.
Expand QA coverage beyond manual sampling by evaluating every customer interaction across supported channels.
Apply customizable scorecards and quality rubrics consistently across teams, programs, and office-specific workflows.
Turn recurring performance patterns into personalized coaching recommendations and practical roleplay training scenarios.
Surface urgent quality issues, compliance concerns, and escalation risks through configurable red flag detection.
AI automation and contact-center software experience guide EmberQA’s platform development.
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.
AI can analyze customer interactions, score them against custom quality criteria, detect sentiment and red flags, search transcripts, extract data, and identify recurring performance patterns. In EmberQA, these capabilities support calls, SMS, emails, and documents. Managers can use the resulting insights to prioritize reviews, improve coaching, identify risks, and understand performance trends more consistently.
Talk with EmberQA about turning interaction data into actionable quality insights.
Connect with EmberQA to discuss your interaction analysis, quality assurance, coaching, and workflow automation goals.
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