Photos, video and delivery · Facial Recognition
Partiu's own facial engine indexes galleries, groups photos by person, and gives each graduate exactly the photos they appear in, in the app, on the portal, and in the studio's pre-selection. The era of "find your photo somewhere in these 5,000 files" is over: AI does hours of work in minutes, and every search is logged for auditing.
The problem and the fix
If any of these situations sounds familiar, it is because they happen in almost every graduation company, until the right system comes in.
After the event, graduates give up looking for their own photos among thousands, and they don't buy what they can't find.
Partiu Facer indexes the gallery by face and shows each graduate, highlighted, only the photos they appear in: a photo found is a photo sold.
The studio team sorts photos by graduate by hand, opening file after file before selection.
Automatic facial pre-selection: each graduate's photos arrive already sorted in the studio's selection, eliminating hours of manual sorting per class.
Third-party facial services charge a lot per photo, have high latency, and leave your biometric data out of your control.
Partiu's own facial engine, with multiple CDNs in Brazil for fast processing, low-resolution indexing to cut the cost per photo, and a search history for auditing.
Photos that fail indexing drop off the radar, and the graduate swears they weren't at the event.
Automatic reprocessing of photos that failed on the first pass: the system keeps trying until the maximum number of faces is indexed, with no manual intervention.
Confirming attendance at events and shoots turns into a paper roll call or a spreadsheet.
Attendance verification at events through facial recognition, using the same indexing base as the galleries.
In practice
Everyday situations at graduation companies, from the problem to the result, using the modules on this page.
A company sold graduation ball photo packages, but conversion was low because graduates had to dig through the entire gallery to find themselves.
With facial indexing, each graduate opened the app and immediately saw their own photos highlighted, with the pre-selection ready to buy.
Purchase rates for packages and individual photos rose steadily in the following classes: when the friction of searching disappears, sales happen on the post-party impulse.
The studio spent two days per class sorting each graduate's photos before opening package selection.
Facial pre-selection automatically grouped the photos by person right after upload, and online selection opened with each graduate's material already sorted.
The two days of sorting went to zero, selection opened the day after the shoot, and the whole cycle (shoot, selection, editing, delivery) got a week shorter.
A season with dozens of events produced enormous galleries, and the company feared an out-of-control indexing bill.
Low-resolution indexing lowered the cost per photo, the engine processed in bulk on GPU, and the cost module showed the billing forecast before the invoice closed.
The company indexed everything within the planned budget, with an immutable log of every charge and actual cost consolidated by class to support pricing.
How it works
Every step is a real module, and what comes out of one goes into the next without anyone typing it again.
Module by module
5 modules and 25 features on this page, all running on the same class, graduate and event records.
In-house facial recognition that is fast and auditable.
The graduate experience: finding their own photos effortlessly.
The sorting the team used to spend days on, ready overnight.
Event attendance confirmation using the same facial base.
Every search logged, every cent explained.
Compare the modules and choose the setup that fits your operation.