QEval
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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Google Cloud Speech-to-Text
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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Voxtral TTS
Voxtral TTS stands out as a cutting-edge multilingual text-to-speech model that excels in crafting exceptionally realistic and emotionally resonant speech from written text, integrating robust contextual comprehension with sophisticated speaker modeling to yield audio output that closely resembles human speech. With a compact design featuring approximately 4 billion parameters, it strikes a balance between efficiency and high-quality performance, making it well-suited for scalable implementation in enterprise-level voice applications. Supporting nine prominent languages along with various dialects, the model can seamlessly adapt to new voices using merely a brief reference audio sample, effectively capturing tone, rhythm, pauses, intonation, and emotional subtleties. Its remarkable zero-shot voice cloning functionality enables it to emulate a speaker's unique style without the need for extra training, and it possesses the ability for cross-lingual voice adaptation, allowing it to produce speech in one language while retaining the accent of another. Additionally, this technology opens up new possibilities for personalized voice experiences across different platforms and applications.
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Gemini 2.5 Pro TTS
Gemini 2.5 Pro TTS represents Google's cutting-edge text-to-speech technology within the Gemini 2.5 series, designed to deliver high-quality and expressive speech synthesis tailored for structured audio generation needs. This model produces lifelike voice output that boasts improved expressiveness, tone modulation, pacing, and accurate pronunciation, allowing developers to specify style, accent, rhythm, and emotional subtleties through text prompts. Consequently, it is ideal for a variety of uses, including podcasts, audiobooks, customer support, educational tutorials, and multimedia storytelling that demand superior audio quality. Additionally, it accommodates both single and multiple speakers, facilitating varied voices and interactive dialogues within a single audio output, and supports speech synthesis in various languages while maintaining a consistent style. In contrast to faster alternatives like Flash TTS, the Pro TTS model focuses on delivering exceptional sound quality, rich expressiveness, and detailed control over voice characteristics. This emphasis on nuance and depth makes it a preferred choice for professionals seeking to enhance their audio content.
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