Keatext

Keatext is an AI-powered text analytics platform that unifies surveys, reviews, and support tickets into a single view, delivering dashboards, sentiment analysis, and automated recommendations to help CX teams act on customer feedback faster.

Keatext is a customer feedback analysis platform built for teams that need to turn unstructured text from surveys, public reviews, and support tickets into a single, coherent view of the customer experience. Rather than relying on a generic LLM, Keatext positions itself as a purpose-built voice-of-customer solution with a dedicated reporting layer, reproducible results, and automated recommendations. The platform is designed to help customer-centric businesses understand end-to-end journeys, improve conversion and activation, increase retention, and deliver a better user experience. The product centers on three pillars: dashboards, drivers and recommendations, and integrations. Dashboards are generated by AI and surface blind spots, themes, and sentiment across every connected channel. The drivers and recommendations engine centralizes feedback into one analytical engine that identifies the key drivers of satisfaction and highlights emerging themes, effectively converting raw sentiment into strategic priorities. Integrations handle the data ingestion problem, with deep connections to platforms like Zendesk and the ability to sync surveys, reviews, and support tickets automatically. In practice, Keatext is aimed at CX leaders, product managers, and support operations teams who already collect feedback but lack the time or tooling to analyze it consistently. The plug-and-play setup means insights are available quickly: case studies describe processing thousands of reviews in minutes and reducing time to insight by 98 percent. For organizations weighing a DIY approach with ChatGPT or similar tools, Keatext argues that generic models offer only basic sentiment analysis and lack the reporting consistency required for enterprise-level decision-making. Keatext fits among dedicated voice-of-customer and text analytics platforms rather than general-purpose AI assistants. Its focus on multi-channel analysis, automated reporting, and recommendation-driven workflows makes it a stronger fit for recurring feedback programs than for one-off text classification tasks. Buyers should note that pricing and trial details are not published on the homepage, so a demo request is the practical first step.