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Diversio collects demographics, inclusion, engagement, and equity data through an anonymous employee survey, then surfaces the benchmarks, AI-generated recommendations, and compliance-ready reports your organization needs to make confident, accountable decisions
Disengagement & quiet exits cost millions in lost productivity & replacement costs.
Regulators, investors, and procurement teams expect clear data on workplace equity & pay transparency
Leaders often lack clear benchmarks and practical insights to guide decisions
on culture and inclusion.
Policies, training & analytics run in isolation, creating efforts that fail to drive change.
Platform is available at three tiers, for organizations running their first inclusion survey to enterprise teams managing multi-region compliance and executive reporting.
Diversio’s proprietary Inclusion Framework™ was developed in consultation with industry bodies, government, equity-seeking group associations, academics, and senior executives. Every survey, score, and recommendation is grounded in this framework.
Diversio’s AI-powered recommendation engine identifies priority areas and gives your leadership team a credible, evidence-based strategy to act on.
See how Mitacs embedded equity across Canada’s innovation structure
Capture qualitative and quantitative inclusion data, surface systemic patterns through NLP analysis, and translate results into prioritized action plans.
See how Hyundai Auto Canada prioritised onsite mental health
Assess DEI across portfolios using a data-backed framework. Benchmark against industry peers, and demonstrate accountability to LPs and stakeholders.
See how Oakley Capital drove DEI impact with data
Track DEI progress across business units with executive dashboards and board-ready reporting. Manage legal and reputational risk before they escalate.
See how Financial Plus Credit Union advanced equity through community
DEI data pulled from HRIS or employee surveys that help leaders understand if action is needed within their organization while providing a deeper understanding of their teams. This data can be used to identify existing biases, gaps, or issues and work to improve them.