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Data That Makes Models Fluent
Collection, annotation, red-teaming and evaluation in 380+ languages — the fuel for AI that works for everyone.
What the service entails
Models are only as good as the data behind them — and most data is English-first. Our global contributor network collects prompts, speech and judgments in your target languages, while trained annotators label, rank and verify at scale.
Evaluation teams then stress-test your models for fluency, factuality, safety and cultural fit, delivering scored findings your engineers can act on immediately.
What's included
- Data collection — prompts, utterances, images and documents sourced per spec.
- Annotation & ranking — labeling, preference judgments and red-teaming by trained raters.
- Model evaluation — fluency, factuality and safety scoring across locales.
- Quality assurance — consensus checks, audits and agreement metrics on every set.
From spec to shippable dataset
Specify
Guidelines, edge cases and acceptance thresholds are agreed up front.
Collect
Vetted contributors produce and label data to your guidelines.
Verify
Multi-rater consensus and audits filter noise before delivery.
Evaluate
Your model is scored against the set, with findings per locale.
AI Data FAQs
How do you ensure annotator quality?
Screening tests, paid pilots, consensus requirements and continuous audits. Raters who drift are retrained or replaced.
Can you handle low-resource languages?
Yes — that is our specialty. Our community network reaches native contributors where crowd platforms cannot.
Who owns the resulting data?
You do, with full rights assigned on delivery and source records retained for audit.
How fast can you scale?
Pilot cohorts start within days; production workforces scale to thousands of contributors with weekly throughput reporting.
Pairs well with
Train on better data
Share your spec — we will propose a pilot dataset within days.