Workflow Guides

Tag peloton and gran fondo photos when bib numbers sit on the back of the jersey, hidden by saddle bags. An honest cycling tagging workflow.

The complete workflow for tagging DTM and GT racing photos with AI. Handle multiple classes, gentleman-driver packages, and reflective-wrap glare with less manual sorting.

Tag karting race photos faster. Handle hand-written numbers, DIY placement, mud-covered karts, and same-day parent delivery with an AI-assisted workflow.

Tag marathon photos by bib number with AI. Handle multi-runner finish-line frames, folded and wet bibs, and same-day delivery — honest about what gets flagged.

A practical workflow for tagging MotoGP, Moto2, and Moto3 race photos. Match detected race numbers to your three start-lists, review the hard reads, and deliver per class.

The complete workflow for tagging NASCAR race photos with AI: match detected car numbers to your start-list, tag pack-racing shots, and deliver faster.

The workflow for tagging WRC and rally race photos with AI. Handle remote stages, mud-covered car numbers, one-pass-per-stage shooting, and end-of-day delivery from base camp.

The complete workflow for tagging World Superbike (WSBK) photos with AI: detect bike numbers, match them to your entry list, and write metadata.

Tag open water and pool swimming photos efficiently. A practical workflow for curved cap numbers, water spray, and cross-referencing your entry list.

The workflow for tagging track day and club racing photos: handle temporary numbers, no official entry list, mixed road and race cars, and same-day delivery.

A practical workflow for tagging triathlon and Ironman photos across swim, bike, and run — three bib positions, transition chaos, and where AI honestly helps.

The complete workflow for tagging World Endurance Championship and Le Mans 24h race photos with AI. Handle thousands of photos across day-night-dawn lighting, multiple classes, and driver changes.

F1 weekends mean hundreds of photos per session and tight wire-service deadlines. Here's how to batch-tag car numbers per session and deliver fast.

Marathons generate tens of thousands of photos, and revenue follows how many you can tag and deliver fast. Here's how to batch-tag bib numbers at scale.

Cycling bibs sit on the BACK, hidden by saddle bags and bidons, and peloton density makes riders hard to isolate. Here's how we tag them and where it's hard.

MotoGP fairing numbers compress at extreme lean, riders hide them, and three classes overlap. Here's how AI vision plus your start-list reads numbers OCR can't.

F1 entry lists change late, wildcards get added, and team names shift with sponsorship. Here's how to match detected car numbers to your own start-list CSV.

Triathlon athletes carry different race numbers per leg. Here's how to match detected numbers to your start-list CSV across swim, bike, and run in one workflow.

Wire-service F1 photographers deliver within hours, not days. Here's how AI tagging of car numbers and drivers helps you cut the manual bottleneck and deliver sooner.

MotoGP weekends run three classes with separate, overlapping delivery deadlines. How to tag and sort per-class galleries fast without mixing classes.

F1 photographers shoot thousands of frames per weekend, each needing metadata. Here's how RaceTagger reads car numbers and writes them into IPTC/XMP.

A marathon means thousands of photos that each need participant metadata so runners can find and buy them. Here's how AI tagging makes a searchable archive.

Cycling pelotons pack riders together, with bibs on their backs and overlapping in the frame. Here's how AI detects and tags every visible bib at scale.

Marathon finish lines put many runners in one frame, and tagging only the leader loses the rest. Here's how AI detects and reads every visible bib in a photo.