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    Chattermill uses cutting edge artificial intelligence to analyse customer feedback across customer touchpoints for organisations to harness customer insights at scale, boost customer loyalty and brand advocacy. They combine machine learning with a deep understanding of a company and their customers, seamlessly integrating with any system used to collect feedback. They then deliver precise, actionable insights enabling their partners to have a complete, objective understanding of their customers every day.

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    Keatext helps businesses cultivate meaningful relationships with their customers by providing them with instant clarity on what customers care about most, and by increasing their ability to respond rapidly to customer needs. Their AI-powered platform synthesizes in seconds large volumes of feedback from multiple channels (such as open-survey questions, online reviews and social media posts) to produce actionable insights delivered on one comprehensive dashboard. Designed to minimize response time, Keatext is the industry’s most agile cloud-based opinion-analysis engine, relying on deep learning and a rich, ever-growing knowledge base. Keatext requires no setup, and features multilingual analysis and context-sensitive, industry-agnostic understanding, as well as real-time visualization of correlations and trends with immediate report-sharing capabilities.

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    NICE Systems is the worldwide leading provider of software solutions that enable organizations to take the next best action in order to improve customer experience and business results, ensure compliance, fight financial crime, and safeguard people and assets. NICE’s solutions empower organizations to capture, analyze, and apply, in real time, insights from both structured and unstructured Big Data. This data comes from multiple sources, including phone calls, mobile apps, emails, chat, social media, video, and transactions. NICE solutions are used by over 25,000 organizations in more than 150 countries, including over 80 of the Fortune 100 companies.