SBX is an innovator in Data-Centric computer vision

OVERVIEW

SBX was founded in 2020 to address the largest blocker to advanced computer vision : Data. Excited by the potential of computer vision and deep learning, the founders wanted a solution that would unblock teams looking for the right data. Digital simulation and generated data is the key to accelerating real-world computer vision.

MISSION

Our mission is to accelerate computer vision in the 21st century. Deep learning is a key technique for advanced perception, but it is often blocked on getting the right training data.

Our goal is to deliver the value of synthetic data as easily and quickly as possible to teams building next-gen computer vision.

VALUES

We value the autonomy to creatively solve problems with the responsibility to deliver great results.

We believe data-driven thinking and analysis helps separate fact from opinion.

Collaborative team problem solving produces the best solutions. Teams work best when discussions are inclusive and everyone can give and receive critical feedback.

Our team

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Ian Dewancker

CEO

Ian Dewancker

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Josh Kuntz

CTO

Josh Kuntz

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Eduardo Hulshof

Tech Art Director

Eduardo Hulshof

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Logan Fairbairn

Technical Artist

Logan Fairbairn

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Sava Nozin

Technical Artist

Sava Nozin

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David Dunkelman

Technical Artist

David Dunkelman

Your Data Partner for Computer Vision

We are a team of industry veterans from robotics, VFX, gaming, and machine learning. Our primary focus is getting your vision team the data it needs to build and improve models core to your products and services.

What Customers say

John Novak
Head of Computer Vision

"With SBX synthetic data, we hope to never use real data again!"

Dave Weatherwax
Senior Director of Software

“SBX generates high fidelity synthetic data with a rapid turnaround time”

James Servos
Perception Team Manager

"SBX kickstarts projects far faster than real-world data acquisition and labeling."

Daniel Grollman
Lead R&D Engineer, PhD

"SBX showed us synth data is viable for our AI needs. We look forward to working together."

Marek Cygan
CTO

"The ability of models trained on SBX data to generalize on fairly diverse items is impressive."

Tarik Kelestemur
Researcher

"Our model trained on SBX data significantly outperformed one trained on data we collected."