Explorance MLY is a SaaS solution that leverages advanced AI and machine learning models to automate the analysis of qualitative feedback, transforming unstructured comments into actionable insights for decision-makers in education and workplace settings. Purpose-built models for higher education, HR, and L&D enable nuanced sentiment analysis, topic categorization, and the identification of recommendations and alerts. MLY processes feedback from any platform, rapidly distilling millions of comments into domain-specific topics, sentiment trends, and forward-looking recommendations. The platform’s Redaction Module automatically removes offensive language, personal names, and sensitive content, fostering psychological safety and inclusivity. MLY supports multilingual analysis, summary reporting, and decentralized investigation, empowering organizations to respond quickly to stakeholder needs, improve teaching and workplace environments, and drive continuous improvement. Trusted by leading institutions, MLY is designed for organizations handling large volumes of qualitative data and seeking to reduce manual effort, enhance data-driven decision-making, and protect stakeholder well-being.

Key Features

AI-Powered Sentiment and Topic Analysis Automatically identifies sentiment, domain-specific topics, and trends in qualitative feedback.

• Tailored models for education, HR, and L&D
• Uncovers positive/negative patterns and unmet needs

Automated Recommendations and Alerts Generates actionable recommendations and highlights urgent issues for rapid response.

• Crowdsourced suggestions for improvement
• Real-time alerts for sensitive or critical feedback

Redaction Module for Psychological Safety Automatically redacts offensive language, personal names, and sensitive content.

• Promotes honest, open feedback
• Protects faculty and employee well-being

Multilingual and Summary Analysis Supports feedback analysis in multiple languages and provides summary insights.

• Enables global deployment
• Delivers concise, actionable reports

Decentralized Investigation and Sharing Facilitates local analysis and sharing of insights across teams or departments.

• New sharing features for distributed analysis
• Supports collaborative decision-making

Scalable Processing and Integration Handles millions of comments and integrates with existing feedback platforms.

• Processes large datasets efficiently
• Compatible with major survey and feedback systems

Benefits

Accelerated Decision-Making Enables rapid, data-driven responses to stakeholder feedback.

• Reduces manual analysis time
• Supports timely interventions

Enhanced Psychological Safety and Inclusivity Fosters safe environments for honest feedback and protects well-being.

• Redacts harmful content automatically
• Encourages open participation

Continuous Improvement and Engagement Drives ongoing enhancement of teaching, learning, and workplace culture.

• Provides actionable insights for improvement
• Increases stakeholder engagement

Operational Efficiency Automates feedback analysis and reporting at scale.

• Minimizes manual effort
• Centralizes and streamlines feedback workflows