We close the data loop for computer vision, so teams spend less time collecting and labeling, and more time shipping models that actually work in production.
Origin
Synthgen was founded in late 2024. We started it as a student project, kept shipping after graduation, and turned a capstone into a company.
Computer vision teams spend 80% of their time collecting, cleaning and labeling data, and 20% training models. That ratio is backwards. Synthetic data plus AI labeling fixes it.
Today we run pilots in agriculture and robotics from the Netherlands, and work with OWOW and SPARC on scaling to every vertical where labeled pixels are the bottleneck.
What we believe
01
We live at the edge of vision AI research — diffusion, zero-shot detection, synthetic augmentation. What lands in a NeurIPS paper this quarter ships in the product the next.
02
AI is a product rule and an operating rule. We build it, we run on it. Leverage compounds when the team that ships the loop also lives inside one.
03
Real-world data only captures the past — edge cases in production send teams back to collect for months. Synthetic plus a small set of real beats real-only, at a fraction of the cost and time.
By the numbers
Every module wired end-to-end. Cut data collection and labeling hours — iterate and ship models faster.
