Eclipse AI

• Unified feedback data ingestion (surveys, reviews, chat logs, emails)

• Multi-channel integration (API, CSV upload, connectors)

• Generative AI insight summarization and action suggestions

• Predictive churn risk scoring

• Conversational “ask your data” interface

• Custom dashboards & KPI tracking

• Sentiment & topic detection across feedback

• Root cause analysis of customer pain points

• Alerting & trend detection for emerging issues

• Role-based access and team collaboration

Eclipse AI is an advanced AI-driven customer feedback analytics platform designed for businesses seeking to convert scattered customer voice data into meaningful actions. It gathers and unifies feedback from surveys, support logs, reviews, chat transcripts, social mentions, and more into a single view. The system then applies natural language processing, deep learning, and generative AI to surface trends, insights, and recommendations that help teams act on feedback faster.

By integrating multiple feedback sources and providing a conversational interface, Eclipse AI allows users to ask questions like “What are the top pain points for churn risk this month?” or “Which topics drive satisfaction in product feedback?” The platform also scores customers based on churn risk, highlights root causes of dissatisfaction, and issues alerts when negative sentiment or anomaly patterns emerge. The dashboards are customizable and tied to KPIs, enabling stakeholders across marketing, product, success, and operations to see relevant metrics at a glance.

Eclipse AI is built on a freemium model: companies can start with a free plan, then scale into paid tiers that support more users, higher volume, and advanced features. It is hosted on AWS infrastructure and supports secure integrations via REST API, enabling seamless embedding into existing tech stacks.

Its core mission is to democratize customer experience intelligence, enabling small and medium businesses to benefit from what was previously expensive enterprise analytics. In practice, early adopters report substantial time savings in manual analysis, measurable reductions in churn rates, and a 60 % improvement in CX metrics within a year.