Data That Actually Works
Founded by a computer vision veteran who's been on both sides of the data pipeline. We understand what makes training data work because we've built the models that depend on it.
Our team combines deep AI engineering experience with hands-on annotation expertise, delivering precise datasets for projects of any scale. Contact us to discuss your data requirements or see our quality standards in action.
Our Story
Most engineers hate dealing with datasets. We actually love it.
After a decade in computer vision engineering, we've watched the same pattern play out countless times. Engineers get excited about architectures and algorithms, then quickly delegate data gathering and annotation to someone else. They want to focus on the "interesting" technical challenges.
That's a costly mistake.
Your data doesn't just feed your model, it fundamentally limits what your model can achieve. The most sophisticated architecture in the world can't overcome poor training data. It's like putting low-grade fuel in a race car and expecting peak performance.
We've seen production-level models fail not because of algorithmic issues, but because someone treated data preparation as a checkbox rather than the foundation it actually is. The filtering wasn't rigorous enough. The annotations missed edge cases. The diversity wasn't there.
So we decided to do what most engineers avoid: make data preparation our specialty.
While others optimize neural networks, we optimize the fuel that powers them. Gathering, preparing, filtering, and annotating data isn't just something we're good at—it's something we genuinely enjoy. Because when the data is right, everything else follows.
We handle the part of AI that most people want to skip, so your algorithms can actually reach their potential.
Setting the new standard for data handling - from diverse gathering to annotating.
Our Services
Discover our range of services designed to meet your data needs. From concept to implementation, we offer comprehensive solutions tailored to optimize your processes and elevate your business.
Consulting
Data Analysis
Our data consulting helps you avoid the costly mistakes we've seen teams make with training datasets. We audit your current data pipeline and provide actionable recommendations to improve quality, diversity, and annotation processes.
We analyze your existing datasets to catch the problems that only surface during production: label inconsistencies, coverage gaps, and edge cases your current data misses. You get actionable insights to strengthen your training data before investing in model development.
Data Gathering
Data Annotation
We design and execute data collection strategies that capture the diversity your models actually need in production. From identifying edge cases to sourcing representative samples, we build datasets that reflect real-world conditions rather than lab assumptions.
We annotate data the way engineers want it done, with rigorous quality controls, consistent labeling standards, and the technical context to catch issues that break models in production. Every dataset comes with transparency into our process and quality metrics.
Get in Touch
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We’re happy to hear from you. Contact us today to learn more about our business and how you can benefit from working with us.