A fully developed, open-source digital ecosystem for public health and educational organizations working with minors. We provide a scalable CRM, close the epidemiological data gap, and build capacity through AI—100% free of venture capital obligations.
Every participant gets a dedicated, secure application. Together, they form a continuous public-health infrastructure.
The foundation of the territorial model is continuous family support. Teenology provides guided check-ins, offline de-escalation cards, and family mediation. It operates on mutual trust, ensuring privacy without surveillance.
School psychologists receive an AI-assisted workspace to handle automated testing, case analysis, and document generation. Schools also receive ready-made integration pages (widgets) to embed AI consultations directly into their websites.
School directors, district coordinators, and regional ministries access anonymized macro-telemetry. By understanding territorial trends and risk heatmaps, institutions can adjust prevention programs proactively, fully respecting individual data privacy.
Built upon a master's level public-health curriculum, our integrated Academy ensures all specialists develop the competencies needed to use AI ethically and effectively for youth prevention.
Prevention-AI resolves the critical bottlenecks in state prevention systems through a unified, AI-driven public health approach.
A ready-to-use, scalable CRM system connecting the electronic workspaces of all participants in the adolescent deviance prevention system.
Eliminates the epidemiological data gap by integrating apps for parents, teens, schools, and government authorities into one secure flow.
Develops the competencies of all specialists via an integrated educational course on health psychology and program development.
Automatically generates detailed statistical pools describing various aspects of psychologists' activities, far exceeding standard departmental reporting.
Creates a continuous "evidence factory" for AI-provided psychological support through big data analysis and constant evaluation of AI protocols.
Forms a territorial system of deviance prevention at any level via a hierarchy of dashboards—from a school psychologist to the UN level.
The Prevention AI engine delivers an unprecedented suite of clinical and educational tools, empowering specialists to operate at the highest standards of international practice.
Conduct Functional Behavioral Assessments (FBA) to identify behavior triggers, and instantly generate structured Behavior Intervention Plans (BIP).
Run automated Manifestation Determination Reviews (MDR/ППк) to analyze if disciplinary issues are linked to a student's underlying health conditions.
Draft comprehensive psychological characteristics and student profiles in minutes, synthesizing observational data into structured professional formats.
Aggregate year-long intervention metrics, consultation statistics, and diagnostic outcomes into official annual compliance reports effortlessly.
Compile complex case histories, intervention results, and diagnostic streams directly into fully structured, official DOCX documents and plans.
The true value of Prevention AI lies not just in its interface, but in its Cognitive Core—a scalable, deterministic AI architecture governed by strict clinical taxonomy and hierarchical prompt engineering.
Unlike standard AI search wrappers that suffer from context pollution as data grows, our engine utilizes deterministic filtering and hierarchical protocols (FBA, MDR, IEP). This means the more we invest in expanding the methodological prompt library and knowledge base, the more precise and clinically safe the system becomes. By investing in this cognitive engine, organizations are essentially digitizing and scaling global institutional memory (WHO and UNESCO standards) into machine logic, making world-class expertise accessible to every school specialist.
We separate public health infrastructure from commercial services to ensure that the core platform remains a true Digital Public Good, free from venture capital debt.
The core infrastructure—including local case journals, document workflow engines (SOAP/IEP forms), and supervised interactive modules in the AI Academy—is 100% free and open-source. This ensures that every specialist and educational institution has access to modern tools and training without any financial burden or vendor lock-in.
Advanced AI-assisted case analysis and real-time document drafting co-pilots operate on a paid subscription basis. This model directly covers the ongoing LLM token and cloud inference costs, making the DPG infrastructure self-sustaining.
Roman Dubrovsky, PhD brings 25+ years of experience in youth prevention, public health policy, and social research. His international track record includes serving as a lead scientific methodologist for UNODC initiatives, coordinating UN/ESPAD global epidemiological reporting, and integrating WHO public health standards into academic curricula.
To ensure alignment with Digital Public Good (DPG) principles, the entire platform architecture—including the Teenology app and specialist terminals—was independently self-funded to the MVP stage. It is 100% free of venture capital obligations or commercial commitments.
The system is designed for an explicit operational handover: Roman serves as the technical Core Maintainer, while looking for institutional partners (like UNICEF) to provide clinical governance, localization, and regional deployment oversight.
ORCID ID: 0000-0001-9876-9798