
Montreal, Quebec – March 2025 – Explorance MLY enables higher education institutions and organizations to transform qualitative feedback into actionable intelligence. MLY 3.3 enhances your ability to explore feedback dynamically, scales analytical consistency across teams, and ensures every user can participate fully — while maintaining alignment with accessibility standards and operational excellence.
As feedback volumes grow and the demand for rapid, nuanced understanding increases, this release addresses your need for flexible exploration, organizational efficiency, and inclusive design. MLY 3.3 helps your teams investigate insights more deeply, maintain analytical consistency, and deliver inclusive, accessible experiences for every user.
MLY 3.3 delivers focused enhancements across exploration flexibility, organizational collaboration, accessibility, and platform infrastructure. Together, these updates make MLY more adaptable, inclusive, and efficient for institutions at any scale.
Understanding qualitative feedback at scale requires both flexibility and consistency—teams need to explore dynamically while working from shared analytical frameworks. With MLY 3.3, we've strengthened the balance between individual exploration and organizational standardization, while ensuring that every user can participate fully. This release empowers institutions to scale text analytics responsibly, accessibly, and efficiently.
— MLY Product Management Team
MLY 3.3 introduces temporary filtering capabilities on Summary and Overview pages, enabling users to investigate further without modifying the default dashboard experience.
This enhancement supports deeper, on-demand analysis while keeping core views simple and accessible for all stakeholders. Users can gain clearer insights in the moment, then return to the standard view, maintaining organizational consistency while enabling individual flexibility.
With Global Custom Analysis, organizations can now create and manage custom topic configurations at the institutional level. These shared analyses can be deployed across teams, ensuring consistent frameworks, definitions, and methodologies throughout the organization.
By eliminating the need to recreate analyses individually, this capability reduces duplicated effort, promotes analytical standardization, and helps institutions scale their text analytics practices efficiently as feedback volumes and user bases grow.
MLY 3.3 aligns with the Web Content Accessibility Guidelines (WCAG) 2.2 Level AA standards, ensuring an inclusive, consistent experience for all users regardless of ability.
This readiness supports broader institutional adoption—particularly in higher education and government environments where accessibility compliance is essential—while reinforcing organizational commitment to equity and inclusion across all feedback and analytics workflows.
MLY 3.3 includes infrastructure improvements that enable hosting within Explorance's optimized data centers. These enhancements deliver faster platform performance, improved reliability, and reduced operational costs, supporting a more sustainable and scalable delivery model as organizational feedback needs continue to expand.
MLY 3.3 is more than a feature update—it's a strategic enhancement that strengthens your qualitative insights ecosystem's flexibility, consistency, accessibility, and operational efficiency.
As qualitative feedback becomes increasingly central to institutional decision-making, MLY 3.3 ensures your teams are equipped with the dynamic exploration tools, shared analytical frameworks, and inclusive design needed to understand voices confidently and act with clarity across every feedback source.
Explorance MLY, pronounced mi-lee, is an award-winning AI-powered feedback analytics platform that transforms open-ended comments from any source into clear, actionable insights. Using Explorance’s pre-built machine learning models, MLY categorizes qualitative feedback into relevant topics, detects sentiment, redacts sensitive content, highlights recommendations, and flags critical issues—all with exceptional speed and accuracy.
