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List of NICE Real-Time Speech Analytics Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight Insight Source
Alorica Professional Services 115000 $15.0B United States Nice Systems NICE Real-Time Speech Analytics Speech Recognition AI 2018 n/a In 2018, Alorica deployed NICE Real-Time Speech Analytics, a Speech Recognition AI application, with an initial implementation running from September 2018 to January 2019. The NICE Real-Time Speech Analytics implementation was scoped to automate quality assurance workflows across Alorica and selected business partner operations, leveraging speech transcription, automated scoring, and exception detection to instrument machine-assisted QA processes. Operational design centralized machine performed QA into existing contact center QA workflows and shifted sampling and review toward analytics-driven scoring and alerts. Machine performed QA accuracy was reported better than 90% when compared to human performed QA, and governance changes included updating QA review rules and operational handoffs to align with automated scoring during the September 2018 to January 2019 rollout.
Atento Professional Services 10400 $1.0B Spain Nice Systems NICE Real-Time Speech Analytics Speech Recognition AI 2020 n/a In 2020 Atento implemented NICE Real-Time Speech Analytics to add real-time interaction intelligence into its customer experience technology footprint. The deployment was categorized under Speech Recognition AI and positioned the NICE Real-Time Speech Analytics application as a core analytics layer within Atento's partner ecosystem alongside Microsoft, SAP, Avaya, and Keepcon. The implementation configured NICE Real-Time Speech Analytics for continuous speech-to-text transcription, real-time keyword spotting and phrase detection, sentiment and silence monitoring, and agent assist event generation. Transcription and analytic outputs were channeled into monitoring dashboards and quality assurance workflows to enable interaction tagging, supervisory alerts, and routed records for post-call review. Integrations referenced in the implementation narrative included Avaya for cloud contact center session capture, Nice Systems for speech analytics and workforce management interoperability, and Keepcon for social media text analytics consolidation to unify interaction records. The operational coverage emphasized contact center operations, quality assurance, workforce management, and customer experience functions across Atento's service lines. Governance and process changes focused on instrumenting real-time monitoring feeds into QA and supervisor workflows, creating event-driven alerts for compliance and CX issues, and aligning workforce scheduling signals to interaction-level analytics. Rollout and systems integration were executed through Atento's partner-managed integration model leveraging existing contact capture points and vendor integration capabilities.
Ausrion Professional Services 23000 $9.0B United States Nice Systems NICE Real-Time Speech Analytics Speech Recognition AI 2016 n/a In 2016, Asurion implemented NICE Real-Time Speech Analytics from Nice Systems (NASDAQ: NICE) across its customer service operations. The deployment replaced LiveEngage and established NICE Real-Time Speech Analytics as the enterprise Speech Recognition AI capability for real-time interaction monitoring across multiple lines of business. The implementation focused on core Speech Recognition AI capabilities, including real-time speech analytics, streaming automated transcription, sentiment detection, and agent assist functionality to surface live conversation intelligence. Configuration emphasized low-latency processing and event tagging to support supervisor monitoring, coaching workflows, and operational alerting tied to customer intents. Deployment scope covered multiple lines of business within Asurion’s customer service organization, creating an operational analytics layer that ran alongside agent desktops and live handling workflows. Architecture concentrated on in-line, real-time processing of voice streams to deliver immediate visibility to supervisors and to drive standardized operational handling across distributed teams. Governance included centralized configuration of analytics rules and vocabulary to align speech models with Asurion-specific terminology and intents, enabling consistent enforcement across business units. NICE Systems reported the solution was successfully deployed and enhancing customer service, reflecting improved real-time visibility into customer interactions.
Communications 94500 $55.1B United States Nice Systems NICE Real-Time Speech Analytics Speech Recognition AI 2018 n/a
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FAQ - APPS RUN THE WORLD NICE Real-Time Speech Analytics Coverage

NICE Real-Time Speech Analytics is a Speech Recognition AI solution from Nice Systems.

Companies worldwide use NICE Real-Time Speech Analytics, from small firms to large enterprises across 21+ industries.

Organizations such as Charter Communications, Alorica, Ausrion and Atento are recorded users of NICE Real-Time Speech Analytics for Speech Recognition AI.

Companies using NICE Real-Time Speech Analytics are most concentrated in Communications and Professional Services, with adoption spanning over 21 industries.

Companies using NICE Real-Time Speech Analytics are most concentrated in United States and Spain, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of NICE Real-Time Speech Analytics across Americas, EMEA, and APAC.

Companies using NICE Real-Time Speech Analytics range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 0%, and global enterprises with 10,000+ employees - 100%.

Customers of NICE Real-Time Speech Analytics include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified NICE Real-Time Speech Analytics customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Speech Recognition AI.