Identif

Updated: August 28, 2026

Identif represents a comprehensive technical challenge, encompassing the development of a mobile application and the creation of a robust backend architecture to structure, verify, and distribute specialized data derived from OSINT (Open Source Intelligence).

It is a global platform dedicated to the learning and visual recognition of vehicles (land, air, and sea) and systems, with a strong military component.

The Project

The goal of Identif is to provide an accessible and portable tool, for both enthusiasts and professionals (intelligence analysts, instructors), to train in visual recognition.

To carry out this project, I designed an architecture divided into two main areas:

  1. The mobile application: A fast, interactive, and offline-ready user interface designed for continuous learning and evaluation.
  2. The administration portal and backend: A custom-built space dedicated to managing a rigorous catalog (technical characteristics, variants, armaments). This portal consolidates automatically gathered OSINT data while enforcing strict human validation to ensure reliability.

This project allowed me to adopt a modular design and tackle exciting challenges such as mobile data synchronization and automating the ingestion of complex information.

The Stack

  • Mobile Application: React Native and Expo
  • Backend and API: Bun and Express.js
  • Database and ORM: PostgreSQL and Prisma
  • Styling and UI: NativeWind (Tailwind CSS) for mobile, React and Vite for the web dashboard
  • Data Management and Caching: React Query
  • Automation: n8n (for scraping and data ingestion via webhooks)

Features

Mobile Application (Users)

  • Interactive Catalog: Exploration of a constantly updated database, including technical specifications, operator countries, and high-quality photo galleries.
  • Advanced Quiz System: Multiple game modes to test knowledge, including a Quick mode, a Custom mode (filtered by domain, difficulty, or origin), and a Survival mode requiring a flawless run.
  • Learning Hub: In development.
  • Offline Resilience: Local caching (via React Query) to ensure that previously viewed vehicles remain accessible, even during network outages.
  • Bilingual Accessibility: Natively translated app in English and French (i18next).

Administrator Space

  • Strict Record Management: Creation and validation of vehicle profiles with data schemas specific to each domain.
  • OSINT Automation: Integration of automated workflows (n8n) to scrape open databases (like Wikipedia) and prepare the verification work for administrators.
  • Data Qualification: Tools for creating and balancing quiz questions, based on a difficulty classification system for images (easy, medium, hard) and platform rarity based on the number of units built (more units built: common, e.g., T-72; fewer units built: rare, e.g., Buffalo MPV).

Feedback and Conclusion

This project, due to its scale, confronted me with several interesting technical challenges:

  • Data Rigor and Typing: The characteristics of military equipment require rigorous structuring. Modeling distinct database schemas for very different domains (air, land, sea) while maintaining global consistency required careful design with PostgreSQL and Prisma. Human validation remains at the heart of the process to certify the data before it reaches users’ phones.

  • Mobile and Offline Optimization: Ensuring a smooth experience on mobile, particularly with loading many high-quality images and handling disconnections. Implementing a solid caching strategy allowed me to offer true resilience to the application.

  • OSINT Processing and Automated Workflows: As the application relies on open sources, integrating webhooks to automate the retrieval of this raw data significantly accelerated the filling of the database. This allowed me to familiarize myself with processing unstructured information and intelligently linking automation tools (n8n) to my Node.js API.

  • Store Deployment: The publication journey on the Play Store, although complex and demanding, allowed me to learn how to deliver a tool that meets modern standards and requirements. Testing phases, version control, and CI/CD automation are areas where I have considerably leveled up.

Identif allowed me to consolidate my full-stack skills by successfully transposing them to the mobile ecosystem, thereby creating an end-to-end mastered product: from gathering raw OSINT data to its interactive delivery to the end user.