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2026 • Engineering Work

Provirium: AI-Guided Automotive Diagnostics Platform

A diagnostics platform for mechanics and workshops that turns symptoms, fault codes, and live vehicle telemetry into provable findings, so parts get replaced based on evidence, not guesswork. Mobile app connects to the vehicle via an OBD adapter; the web dashboard tracks every session, graph, and confirmed repair.

#Laravel 13 #PHP 8.4 #PostgreSQL 17 #Redis 7.4 #Filament 5 #Inertia.js + Vue 3.5 #Tailwind CSS 4 #Laravel Cashier (Stripe) #Laravel Sanctum #Docker #Kubernetes (k3s) + ArgoCD #Cloudflare
Concept & Architecture

Provirium is built around a single principle: "Prove Before Parts." Instead of swapping components on a hunch, mechanics use the platform to capture the exact moment a fault occurs and back every recommendation with data.

How it works:

  • Mobile app + OBD adapter: connects to the vehicle, guides the user through structured diagnostic tests, streams live data, and records the precise telemetry snapshot when a fault triggers.
  • Cloud sync: every diagnostic session uploads automatically; nothing is lost between the shop floor and the office.
  • Web dashboard: workshops review vehicles, full session history, live-data graphs, findings, generated reports, and confirmed repair outcomes in one place.
  • Workshop & team management: multi-user workshops with role-based access (master technician, diagnostic specialist, junior technician, admin), so a shop owner controls who sees and does what.
  • Subscriptions & billing: self-service plans (individual mechanics through full workshops) handled via Stripe, with usage metrics and customer portal.
  • Multilingual: the entire platform and marketing site are available in English, Croatian, German, and Italian, with SEO-optimized translated URLs for each market.

The platform spans a marketing site, a customer dashboard, a full admin panel, and a REST API ready for the mobile app, all running on a self-hosted, automatically-deployed cloud infrastructure.

© 2026 Kristijan Soldo