Eclipse AI Review

Eclipse AI is a customer feedback analytics platform that centralizes reviews, surveys, call data, and support tickets into a single system. Eclipse AI applies AI-driven classification and sentiment analysis to identify themes, track customer experience trends, and surface operational insights across locations and channels.

Eclipse AI connects data sources such as review platforms, surveys, CSV uploads, and communication channels into a unified analytics layer. Eclipse AI normalizes and consolidates this data to provide a single view of customer sentiment and performance across teams, regions, and business units.

Eclipse AI generates AI-driven insights such as sentiment trends, recurring customer issues, and performance patterns across locations. The platform analyzes structured and unstructured feedback to highlight operational gaps, customer pain points, and improvement opportunities in real time dashboards.

Eclipse AI uses free-text sentiment analysis to evaluate customer feedback from reviews, surveys, and call transcripts. The system categorizes sentiment signals and links them to specific themes or locations, enabling teams to monitor experience changes and identify negative trends early.

Eclipse AI processes audio and video call data by generating transcripts and AI summaries. It extracts key topics and sentiment signals from conversations, allowing teams to analyze customer interactions alongside surveys and reviews within the same analytics environment.

Eclipse AI provides customizable dashboards for reviews, surveys, and call analytics. Users configure views by location, channel, or metric, enabling real-time tracking of customer experience KPIs and cross-comparison of performance across multiple business units.

Eclipse AI supports data integration through CSV imports, API access, and connectors such as Zendesk. These integrations enable automated data ingestion from support systems and external feedback sources into a unified analytics and reporting environment.

Teams use Eclipse AI to identify recurring customer issues, monitor satisfaction trends, and prioritize operational fixes based on feedback data. Insights are shared across marketing, operations, and training teams to align improvements with measurable customer experience outcomes.

Eclipse AI includes OSINT capabilities that collect and fuse public data sources for analysis. It supports entity mapping, link analysis, and collaborative investigation workflows, allowing teams to visualize relationships and patterns across external datasets.

Eclipse AI supports multi-location and franchise structures by consolidating feedback data at scale and enabling hierarchical analysis. The platform compares performance across branches, regions, or units while maintaining centralized dashboards and role-based access for different teams.