Koretex is a global labeling network — 4M+ contributors paired with on-device AI doing the heavy lifting. Get the labels you need faster and cheaper than the big platforms, with no minimums and a team that actually picks up the phone.
Robotics data isn't a CSV — it's hours of multi-camera video, telemetry-aligned demonstrations, and trajectory comparisons. Most labeling platforms weren't designed for any of that, and the ones that were charge accordingly.
Koretex was built around it. The model runs on the labeler's device, so video stays local and bandwidth stops being the bottleneck. You can ship 10-hour episodes to thousands of reviewers at once — and get high-agreement labels back in hours, not weeks.
"Video labeling on the major platforms either prices you out or queues you for weeks. Pushing inference to the device collapses both problems at once."
"Your model has to be small, fast, and reliable on-device. Ours is too — we use the same architecture every day. The labels we generate are tuned for the exact constraints your inference runs under."
A growing share of the most consequential AI doesn't get to call a server. Defense systems operating in contested airspace, autonomous vehicles on millisecond loops, surgical robots, healthcare devices, anything air-gapped — all of it has to think locally, decide locally, and be wrong as rarely as physically possible.
Koretex was built around exactly this constraint. Every contributor in our network already runs a small model on their own device — the same problem shape your engineers solve every day. The labels we produce are calibrated for the size, latency, and failure modes that on-device inference actually has to live with.
Scale, Surge, and Snorkel were built for nine-figure enterprise programs. Koretex was built for everyone else — the teams shipping real models on real timelines, with budgets that look like a real startup's.
Need 2,000 labels by Friday? Done. We don't have a sales floor that has to clear a six-figure deal before your task moves.
On-device inference removes the largest hidden cost line in labeling. We pass that through — typically 3–5× cheaper than the incumbent quote, sometimes more.
4M contributors across 80+ countries means the workforce is always awake somewhere. Most tasks finish in hours, not weeks.
Code reviewers see code. Spanish speakers see Spanish. Robotics reviewers see robotics. The model handles the first pass; the right humans handle the rest.
Every batch comes back with gold-set agreement, inter-annotator scores, and per-task uncertainty flags. You see what we're confident in and what we're not.
You'll talk to the founder, not an account exec who's been at the job for three weeks. Tight feedback loop, fast spec changes, real partnership.
Built for: Robotics & physical AI · On-device & edge models · RLHF & preference data · Eval & red-team scoring · Multilingual & multimodal · Vertical fine-tuning datasets
Every labeler in the Koretex network runs a small AI model on their own device. The model produces a draft for each task — frame label, preference pick, segmentation, action boundary, whatever the spec calls for. The human then reviews, corrects, and escalates.
This single architectural choice is the whole game. The marginal cost of inference drops to zero, so we pass the saving through to you. Labeler throughput jumps roughly tenfold, so they earn more per hour and we keep the best ones. And the model gets sharper every cycle your data flows through it.
The result is a labeling network that gets faster, cheaper, and more accurate the more you use it.
I'm Sean. I'm building Koretex because the way labels are priced today still assumes the work has to be done from scratch by a human in a browser. It doesn't anymore — and the platforms that figured this out first will be the ones the robotics and physical-AI wave actually runs on. If labels are on your critical path, I'd love to find out where we can help.
Prefer to write it out? Drop a one-liner over email — task type, rough volume, timeline — and you'll get a reply within a day.
Koretex