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Who We Are
Our team brings together startup scale-ups and exits; scaling from $0–$20M in nine months, with Stanford PhD research in ML, neuroscience, and computational linguistics.
What We Do
Everrett learns reasoning from human experts to automate data annotations surpassing accuracy at scale.
Why We Do It
The real bottleneck in AI isn't compute, it's human expertise. As models grow, high quality data becomes critical. Everrett turns human intelligence into scalable infrastructure, cutting costs, boosting throughput and powering the next generation of AI systems.
How We Do It
Today’s frontier models depend on massive human contractor networks and slow, post-hoc evaluation. Everrett eliminates this entirely, evaluating in real time and delivering superior data in milliseconds.
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