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Transform unstructured voice data into actionable insights.
In today’s competitive landscape, enterprises are turning to AI to drive efficiency and improve customer experiences. Start with the foundation: your voice data.
Customer interactions contain emotional nuances, context, and valuable business insights that traditional analytics miss.
Many organizations struggle to extract meaningful data from voice interactions because:
This is where CXEX’s AutoInsights comes in – a powerful, scalable solution designed to unlock the full potential of your voice data.
Post-call analytics systematically transforms raw voice interactions into structured, actionable insights that drive smarter decisions and superior customer experiences.
Ideal for CRM integration, ensuring valuable insights are consistently captured and leveraged across your organization.
Identify emotional drivers like stress, anticipation, and engagement to improve both customer and employee experiences.
Automatically extract critical call topics, common issues, and emerging trends to enable proactive business improvements.
Skip costly and lengthy internal R&D on speech engine operationalization, speech-to-text accuracy, and model training.
Leverage pre-built, API-ready analytics pipelines to rapidly deploy advanced AI-driven workflows like claims management, retention, and fraud detection.
Although primarily for voice data, AutoInsights' structured outputs integrate with text-based channels like web chat, email, and WhatsApp for a unified customer view.
Deployed securely on AWS, GDPR and ISO 27001 certified, with SOC2 pending. Supports large-scale global operations.
Combines advanced natural language processing, emotion analytics, and domain-specific insights for unparalleled accuracy.
API-first design allows seamless integration with CRM platforms, BI tools, and internal workflows.
Enhanced claims management by feeding structured voice data into existing systems, reducing resolution time by 40%.
Ingested historical conversation outputs to proactively retain 25% more customers.
Improved voice bot accuracy by 35% by incorporating rich call insights, enhancing customer satisfaction.
Trained internal LLMs with structured call summaries, aligning customer interactions with internal resources.