About RaceTagger
We're building the future of professional motorsport photography workflows with AI-powered automation.
Who We Are
RaceTagger was born from frustration.
After spending years as both a web developer and motorsport photographer, I found myself manually tagging tens of thousands of race photos—identifying race numbers, matching them with driver names, organizing folders. Hours and hours of repetitive work that kept me away from the camera and my clients.
I knew there had to be a better way. I started experimenting with the first prototypes back in 2020—completely different in structure and functionality from what RaceTagger is today. After several years of testing, iterating, and rebuilding from scratch, I finally launched the public version in October 2025: a desktop application that uses AI to automatically detect race numbers, match them with your starting lists, and organize everything—so you can get back to what you love: shooting.
RaceTagger runs entirely on your computer (your RAW files never leave your machine), and it's built by photographers who understand your workflow. We're a small bootstrapped team focused on solving real problems, not chasing hype.
The Problem We Solve
The Old Way
- •6-10 hours of manual photo tagging per event
- •Repetitive, error-prone data entry
- •Delayed client deliveries
- •Lost revenue opportunities
RaceTagger's Solution
- •30-45 minutes AI-powered processing
- •99.2% automated accuracy
- •Same-day client delivery
- •More time for creative work & growth
Our Target Audience
We serve professional motorsport photographers who:
- →Shoot races, track days, karting events, or automotive competitions
- →Process hundreds or thousands of photos per event
- →Need to deliver organized galleries to individual drivers/teams
- →Already use Photo Mechanic, Lightroom, or Capture One
- →Value their time and want to scale their business
Our Technology
AI-Powered Detection
Our proprietary computer vision models are trained specifically on motorsport imagery to detect race numbers with 99.2% accuracy—even in challenging conditions like motion blur, poor lighting, or partial occlusion.
Desktop-First Privacy
Unlike cloud-based solutions, RaceTagger runs entirely on your computer. Your RAW files never leave your machine, ensuring complete privacy and security for you and your clients.
CSV Integration
Import starting lists or participant data from any CSV file. RaceTagger automatically matches detected race numbers with driver names, teams, and custom metadata fields.
Workflow Integration
RaceTagger writes professional EXIF metadata directly to your files, making it seamlessly compatible with Photo Mechanic, Lightroom, Capture One, and any DAM system.
Product Development Stage
Current Status: RaceTagger launched publicly in October 2025 and is in active public beta with a growing community of professional photographers using the platform in production environments.
What's Available Today:
- ✓Full desktop application (Windows & macOS)
- ✓AI race number detection with 99.2% accuracy
- ✓CSV driver list import & matching
- ✓Automated EXIF metadata writing
- ✓Smart folder organization
- ✓Support for Canon, Nikon, Sony RAW formats
- ✓100 free analyses per month
Coming Soon (Q1-Q2 2025):
- →Batch processing optimization for 5,000+ photo events
- →Custom AI model training with your specific race series
- →Team collaboration features for photography agencies
- →Mobile app for on-site photo preview & sharing
- →Integrated commercialization platform for photo sales & delivery
Our Mission & Vision
Mission
To eliminate tedious, repetitive work from professional photography workflows, allowing creatives to focus on what they do best: capturing incredible moments.
Vision
To become the essential AI-powered workflow tool for every professional photographer in action sports, motorsports, and event photography—helping them scale their businesses while delivering better, faster service to their clients.
Ready to Transform Your Workflow?
Join 100+ professional motorsport photographers already saving hours with RaceTagger.