The data stack behind frontier models.
We work with foundation model labs from pretraining to alignment — sourcing original multilingual data, running RLHF programs at scale, and building evaluation harnesses that measure what actually matters.
Built for the teams shipping frontier AI.
Foundation model teams have unique data needs: original corpora the web doesn't have, high-quality alignment data that captures nuanced human preference, and evaluation suites that haven't been contaminated by training data.
We're already embedded with frontier labs. Our annotators are research-grade experts — linguists, domain PhDs, safety researchers — managed by teams who understand what an alignment program actually looks like.
What we bring to the table.
Multilingual pretraining corpora
Original-source data across 90+ languages, including low-resource dialects the open web barely covers. Fully licensed, provenance-tracked, and delivered with demographic metadata.
Long-form written content
Essays, reports, instructional text, creative writing across domains.
Conversational corpora
Multi-turn dialogue between matched native speakers, controlled for topic diversity.
Speech & transcription
Hours of captured speech with aligned transcripts, diarization, and acoustic variety.
Code & reasoning
Human-authored code with natural-language explanations and chain-of-thought traces.
Alignment & RLHF
Our alignment teams have shipped RLHF programs at frontier labs. We run preference labeling, critique, rewriting, and red-teaming workflows calibrated against your rubric and rater-drift monitored in real time.
Preference ranking
Pairwise and multi-way preference labels for reward model training.
Free-form critique
Structured written critiques for RLHF and RLAIF pipelines.
Response rewriting
Ideal-response rewrites by domain experts for SFT and DPO datasets.
Adversarial red-teaming
Targeted harm probes, jailbreaks, and edge-case discovery.
Uncontaminated evaluation
We build custom evaluation suites that have never touched a training crawler. Statistical rigor, blind rating, and expert-grade adjudication — so your benchmarks actually mean something.
Custom eval construction
Benchmarks written specifically for you, never published, fully provenance-logged.
Capability scoring
Granular breakdowns across reasoning, safety, factuality, creativity, code.
Head-to-head ranking
Blind model comparisons against competitors or internal variants.
Continuous regression
Running eval programs that flag quality drops on every model update.
Safety & red-teaming
Pre-launch safety audits, policy-compliance evaluation, and structured adversarial testing. Built by researchers who understand modern AI threat models.
Safety evaluation
Policy-compliance scoring against your own harm taxonomy.
Structured red-team
Trained adversarial annotators running targeted probe programs.
Jailbreak discovery
Systematic search for prompt injections, PII leakage, and harmful generation.
Bias & fairness audits
Demographic and cultural bias scoring across multilingual evals.
Where foundation labs use us.
Pretraining corpus expansion
Original multilingual data that expands your training distribution beyond scraped web.
RLHF program operations
Running full alignment programs as an extension of your research team.
Constitutional AI workflows
Critique, revision, and principle-grounded preference data at scale.
Eval suite construction
Contamination-free benchmarks for every new capability you ship.
Safety audits
Pre-deployment red-teaming and policy-compliance scoring.
Low-resource languages
Building representation for languages with minimal internet presence.
Common questions.
Can you handle confidential research projects?
Yes. We routinely work under strict NDAs with dedicated clean-room teams, air-gapped environments, and named-POC-only access. Never had a leak.
How do you prevent benchmark contamination?
Custom datasets written specifically for your eval — never published, never indexed, delivered with full provenance logs proving they never hit a training crawl.
What's the minimum engagement?
Foundation-lab engagements typically start at $250K. We take on smaller mission-aligned work for academic research or novel alignment programs.
Can you scale to 100+ annotators on one project?
Yes. Our largest single-program team was 340 annotators across 6 regions, with ramp-up in 5 business days.
Do you offer exclusivity arrangements?
For certain specialist panels (e.g., security researchers, rare-language experts), yes. Discuss in the first call.
Let's make your AI better together.
Tell us what you're training, aligning, or evaluating. We'll map a delivery plan, staffing model, and timeline within one working week.