Train your own facial recognition model with us.
We capture photos and video, compute facial coordinates, and train the network with manual corrections. Two to four hours is all it takes to build recognition this accurate. Your data stays private — only anonymized vectors remain.
How did a small team build recognition software this precise?
It started with a developer in Amsterdam who wanted face recognition that actually respects the data. Two to four hours of manual training per session, constant corrections, and a commitment to discarding everything except the anonymized vectors.
Who works on your facial coordinates
Every vector and manual correction passes through the same two people before it reaches production. Here they are.
Founder & Lead Developer
Nikita Minin
Nikita builds the neural network and writes the coordinate-mapping software. He personally runs every training session and makes manual corrections when the algorithm misses a point.
Data Processing Specialist
Anika Verma
Anika uploads source photos and videos, validates facial coordinate outputs, and flags mismatches for retraining. She ensures your data stays anonymized and deleted after processing.
What partners say about the 2–4 hour process
Every training session involves manual correction at every step. That is what makes the recognition reliable, and that is what our partners notice.
We were skeptical about the time commitment, but the manual corrections made all the difference. The model now recognizes faces under varying lighting conditions without fail.
Lena van der Meer
Product Manager, SmartVision Labs
The anonymized vector approach sold us. No raw data storage, no privacy headaches — just accurate recognition that keeps getting better with each manual tweak.
Jan Bakker
CTO, SecureEntry Systems
What impressed us most was the transparency. You explained exactly why it takes 2 to 4 hours and what gets corrected manually. No fluff, just honest engineering.
Sofia Rossi
Head of R&D, HomeAccess AI
Our smart doorbell needed reliable face detection across different angles. After training, the network handled profile views and low-light shots better than any off-the-shelf solution.
Thomas Fischer
Hardware Lead, SmartLock GmbH
The 2 to 4 hour training process: what you should know
Ready to start with a face recognition model built for your project?
We begin with a few photos and videos, map every coordinate, and train your network in 2 to 4 hours. Your images are discarded — only anonymized vectors remain.