Prevention was episodic
Families reached specialists too late, specialists worked in isolation, and administrators saw reports after the situation had already changed.
For decades, prevention systems were limited by cost, paperwork and the lack of continuous feedback. AI changes the technical and financial boundary. Prevention AI Platform is built as a hierarchy of applications: support for families, AI workspaces for specialists, and aggregate dashboards for institutions.
The goal is not a chatbot. The goal is a new operating layer for the prevention of risks among growing generations: grounded in public-health evidence, connected to specialist practice, and continuously learning from aggregate, privacy-safe signals.
Families reached specialists too late, specialists worked in isolation, and administrators saw reports after the situation had already changed.
Interviews, diaries, de-escalation and specialist preparation can happen between formal appointments, at a cost that was previously impossible.
Each application is an organ of one system: consumer support, specialist workflow, scientific analytics and territorial governance.
The platform is not driven by generic prompting alone. It already includes a prevention taxonomy, a structured knowledge-base direction and an analytics contour where aggregate events can support research and evaluation.
A seamless flow of data, insights, and support across three critical layers. Each layer respects privacy and ensures ethical AI use.
Free relationship check-up, AI Companion (not therapy), Family Bridge with Privacy Shield, guided sprints (Pulse + Battery), anonymized answer sharing, local diary and offline cards. Built for communication on equal footing — not parental control or surveillance.
Specialists receive an AI assistant for quick consultation, methodological expertise and document drafts. The current specialist interface is already available as the Prevention.AI bot for professionals.
Free AI for classroom teachers, Prevention Terminal for school psychologists, Teenology as the family layer on equal footing — mutual trust, not surveillance. Aggregate dashboards for leadership are the next funding milestone.
The next stage is to finish workstations and dashboards for every administrative level: school director, district coordinator, regional ministry and national prevention administration. Sensitive case data stays local; upper levels receive only aggregate signals.
Built for communication on equal footing — not parental control or surveillance.
Specialists receive an AI assistant for quick consultation, methodological expertise and document drafts.
Privacy-safe telemetry for school administrators and clinic directors to understand macro trends without exposing individual identities.
Deploying AI in mental health requires a profound shift in how professionals interact with technology. Our academy ensures safe, ethical, and effective adoption.
Cloud and startup support would let the project move from implemented parts to a live end-to-end demonstration: long-context AI, scalable inference, specialist account federation, terminals and aggregate dashboards.
Azure/OpenAI credits help scale deep AI accompaniment and move the specialist data layer toward production-grade PostgreSQL infrastructure.
Gemini on Vertex AI for long-context family sessions and specialist workflows; BigQuery for anonymized pilot metrics; Google Antigravity for agentic engineering velocity as a solo founder ships federation, terminals, and safety automation.
Available for Windows. Secure, local, and built for privacy.
Roman Dubrovsky, PhD brings 25+ years of experience in youth prevention, public health policy, and social research.
Career spans from conducting field research on child protection for UNICEF and WHO, advising governments, to managing national school psychology systems. As a CBT practitioner, Roman recognized the critical imbalance between administrative burdens and therapeutic work, leading to the creation of Prevention AI.
ORCID ID: 0000-0001-9876-9798