
Contact center QA teams evaluate 1 to 5% of calls manually. QEval eliminates that bottleneck by applying AI speech analytics and automated scoring to 100% of interactions across voice, chat, and email, using a classification engine trained on 138M+ real conversations.
Capabilities span quality monitoring, compliance detection for PCI, HIPAA, and GDPR at 98% accuracy, sentiment analysis, keyword identification, agent coaching workflows, performance gamification, and predictive analytics across 110+ configurable dashboards. Quality scoring runs at 94% accuracy with zero manual intervention.
Deployment takes 30 days. Industry standard is 90 to 120. No disruption to live operations. Etech Global Services built QEval from two decades of running Fortune 500 contact centers in healthcare, telecom, retail, banking, and BPO. ISO 27001, SOC 2, PCI-DSS certified. Built for QA leaders and operations teams scaling coverage without adding headcount.
QEval also provides call recording management, screen capture, custom evaluation forms, calibration tools for QA consistency, root cause analysis, trend identification, and automated alert systems for compliance breaches. The voice of customer module tracks customer sentiment across touchpoints to identify service gaps and training opportunities. Real-time monitoring lets supervisors intervene during live interactions. Role-based access controls, audit trails, and data encryption ensure enterprise-grade security. QEval supports multi-site and multilingual contact center environments with centralized reporting across locations.
API integrations connect QEval with existing CRM, telephony, and workforce management systems. Automated report scheduling delivers insights to stakeholders without manual effort.
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An API powered by Google's AI technology allows you to accurately convert speech into text. You can accurately caption your content, provide a better user experience with products using voice commands, and gain insight from customer interactions to improve your service. Google's deep learning neural network algorithms are the most advanced in automatic speech recognition (ASR). Speech-to-Text allows for experimentation, creation, management, and customization of custom resources. You can deploy speech recognition wherever you need it, whether it's in the cloud using the API or on-premises using Speech-to-Text O-Prem. You can customize speech recognition to translate domain-specific terms or rare words. Automated conversion of spoken numbers into addresses, years and currencies. Our user interface makes it easy to experiment with your speech audio.
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Higgs Audio / Avatar
Higgs Audio / Avatar represents a versatile suite of foundational audio and avatar technologies that create realistic speech, comprehend tone, emotion, and intent, and provide a visual element to voice interactions. These models encompass capabilities such as text-to-speech, speech-to-text, avatar creation, and smart voice casting, which intelligently chooses a suitable voice based on context, sentiment, and content. Designed for practical use in production environments, Higgs merges expressive generation with strong speech comprehension and adaptable deployment suited for situations where quality, latency, and dependability are crucial. With high-precision multilingual speech recognition across primary languages, the technology also features voice cloning that captures a speaker’s unique tone from brief samples, ensuring brand voice consistency in various interactions. Additionally, sentiment analysis interprets emotional cues in speech, facilitating improved routing, enhanced analytics, and more context-aware agent responses, ultimately leading to a more engaging user experience. This comprehensive approach not only elevates communication but also empowers businesses to connect more effectively with their audiences.
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Vision Agents
Vision Agents is a versatile open-source Python framework designed for developing low-latency voice and video AI agents utilizing any model. This framework empowers developers to integrate large language models, speech recognition, and vision models from over 25 different providers, enabling the creation of real-time agents for applications such as telehealth, voice assistance, live coaching, video analysis, interactive avatars, security surveillance, sports commentary, and a variety of other multimodal uses. Its architecture is tailored to facilitate the development of agents capable of listening, speaking, seeing, processing media, accessing tools, and providing instant responses, all while operating on Stream's expansive global edge network, which ensures latency below 500ms. With just a minimal Python setup, developers can quickly create their first agent by leveraging platforms like Gemini Realtime, OpenAI, Deepgram, ElevenLabs, Stream, or other compatible providers. Furthermore, Vision Agents accommodates both real-time speech-to-speech models and tailored speech-to-text, language processing, and text-to-speech pipelines, allowing teams to either rapidly deploy a functional voice agent or exercise complete control over the components involved in speech recognition, language reasoning, and text-to-speech functionalities. Overall, this framework not only simplifies the process of building sophisticated AI agents but also enhances flexibility and performance across diverse applications.
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