Enterprises face growing challenges in processing and understanding massive volumes of customer feedback scattered across channels like support tickets, call transcripts, CRM logs, surveys, and social media. Traditional LLM-based tools that operate in the public cloud introduce serious privacy risks, compliance concerns, and data governance issues—particularly when handling sensitive conversations that may contain personal or regulated information. As a result, many organizations either forgo sentiment analysis entirely or rely on manual processes that are slow, expensive, and prone to missed insights.
Generate empowers enterprises to securely perform large-scale sentiment analysis entirely within their own controlled environments. By ingesting structured and unstructured customer data—like emails, chat logs, transcripts, and survey responses—Generate uses fine-tuned, private LLMs to deliver precise sentiment summaries without sending data to external providers. It automatically clusters themes, identifies trends, flags emerging concerns, and highlights customer praise, turning thousands of data points into actionable insights. Integrated dashboards, real-time alerts, and reporting capabilities allow teams to track sentiment shifts over time. Crucially, Generate operates fully within private enterprise infrastructure or secure private clouds, ensuring customer data stays confidential and compliant with privacy regulations.
Generate transforms vast amounts of raw, unstructured customer feedback into confidential, actionable sentiment intelligence. It enables enterprises to act on emotional and experiential signals at scale—while keeping customer trust, data privacy, and regulatory compliance at the core of the process.
