Why fund Dzvin.co?

Dzvin.co combines three related experiences: a private personal wellbeing journey, permissioned team analytics, and a controlled research workspace.

Our research opportunity is applying Decision Intelligence to transform observations and risk signals into explainable, human-supervised next actions with stated uncertainty and feedback.

Standalone check-ins and one-off surveys can fragment observations, context and follow-up. A prediction alone does not tell a user or decision maker which safe action is appropriate.

Mental-health AI needs explicit attention to uncertain and incomplete data, human agency, privacy, bias and the actual outcome of decisions.

Individuals who want to observe their personal trajectory; HR and managers who need authorized aggregate context rather than employee surveillance; researchers studying repeated measures and intervention processes.

These are potential beneficiary groups, not existing commercial customers or trial participants.

The software repositories contain user-facing interfaces, backend risk/decision-support modules, research-workspace components, tests and methodological specifications.

These are engineering artifacts, not proof of scalable deployment, validated benefits or revenue.

Complete release/security integration, turn research hypotheses into reproducible protocols, enable responsibly recruited pilots, study usefulness and uncertainty, and prepare a controlled product launch.

Financing should buy a documented reduction in technical, scientific and product uncertainty through specific milestones.

Hypotheses include future B2B service contracts, funded research partnerships and a separately sustainable personal experience.

No sales, pricing validation, customer growth, TAM or ROI is claimed as measured evidence.