Multimodal training data, captured natively across the geographies and languages your AI needs to understand. People on the ground in eight countries. Native depth in six languages.
Collected by field teams in the actual environments your model needs to learn from. Egocentric video, robotics task data, multilingual audio, large-scale visual capture.
Every reviewer is fluent in the cultural context. No translated guidelines, no bridge languages, no proxy judgments.
Engineering, healthcare, legal, finance, and creative. Used for model evaluation, RLHF, output ranking, and gold-standard dataset construction.
Three things make AI work in the real world: the languages it's spoken in, the places it's used in, and the modalities it has to understand. We do all three.
English, Hindi, Spanish, Arabic, French, and Japanese — covered by trained native-speaker networks across collection, annotation, and review.
Additional language communities can be onboarded for projects requiring them.
United States, Canada, United Kingdom, France, Spain, India, Brazil, and the United Arab Emirates. We operate field capture and annotation teams in each of these countries today.
New geographies can be stood up on accelerated timelines when projects require it.
Egocentric video, robotics task data, multilingual audio at scale, and field collection in environments that aren't well-represented in existing training corpora.
Built for the data needs of world-model training, embodied AI, and frontier multilingual systems.
Every engagement begins with a detailed scoping process — defining the data, languages, geographies, modalities, and quality bar, alongside the consent, regulatory, and data-residency framework the program will operate under.
Scoping concludes with a written proposal. We've streamlined this process as much as the work allows; we don't shortcut it, because the front end of a program is where most failure modes are introduced.
Native-speaker audio capture and transcription across multiple languages, delivered for frontier model training programs. Sustained throughput across multi-month engagements with weekly QA gates.
Image and video collection programs spanning multiple countries simultaneously, coordinated against unified specifications. Native field teams, on-site quality leads, integrated review pipelines.
Egocentric video, robotics task data, and physical-world capture in environments selected to widen the diversity of existing training corpora.
Sustained annotation operations running for multiple quarters, covering image, video, and audio modalities, with continuous QA evolution as model needs shift.
Whether it's a single language program or a multi-geography capture engine, we'll scope it with you and propose a calibration pilot.