Foundation
Model Labs
The human intelligence layer for frontier model development — RLHF preference data, multilingual safety evaluation, expert red-teaming, and custom benchmark construction that scales with your training pipeline.
What foundation model teams need from human intelligence
Multilingual RLHF at scale
Preference ranking and SFT data in dozens of languages — with native-speaker reviewers who understand cultural register, not just linguistic correctness. English preference proxies don't transfer.
Safety coverage in non-English markets
Safety red-teaming run exclusively in English misses culturally specific harms and jailbreak patterns in other language markets. Fuzu Atlas provides native-speaker red-teamers in 40+ languages.
Private, non-contaminated benchmarks
Public benchmarks get contaminated with training data. Human-constructed private benchmarks, built to your evaluation spec, provide reliable capability measurement at each training checkpoint.
Domain expert annotation
Medical, legal, scientific, and technical SFT data requires credentialed reviewers — not generalist annotators who can't catch domain-specific errors in training examples.
Multimodal training data
Vision-language model development requires image captioning, VQA datasets, and instruction tuning data at scale — with cultural diversity in image selection and caption authoring.
Ongoing regression evaluation
Models fine-tuned on new data can regress on previously strong capabilities. Human evaluation programs that track quality across training iterations catch degradation before it ships.
Why Fuzu Atlas for foundation model work
Foundation model labs need a human intelligence partner that can operate at the pace of training — not a vendor that requires six weeks of onboarding before the first batch ships.
Fuzu Atlas's pre-validated talent pools in 40+ countries mean language coverage gaps can be addressed quickly. Governance infrastructure — QA authority, audit trail, rubric discipline — means annotation quality doesn't degrade as volume scales.
And unlike platforms that forward-sell capacity they don't yet have, Fuzu Atlas's activation model is designed around operational honesty: scoped PoC, measured ramp, governed program.
Most relevant solutions & use cases
Building the next generation of models?
Start with a scoped PoC — RLHF data, safety evaluation, or benchmark construction — and see quality before you commit to volume.