Human judgment at scale for relevance and quality.

Ranking and ads systems need consistent, high-throughput human judgment that stays calibrated as guidelines evolve. The challenge is maintaining quality and policy consistency across millions of nuanced relevance and safety decisions.

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AI use cases

Where it applies.

Relevance and quality rating
Query and intent labeling
Ad policy enforcement
Ranking evaluation
Content safety review
Preference and side-by-side judgments

Data requirements

What it takes.

Calibrated rater pools
Evolving guideline management
High inter-rater agreement
Throughput with quality gates
Locale and language coverage
Drift monitoring

Relevant data products

Products that map to this work.

Data Product

Model Integrity & Evaluation

Private benchmarks, hallucination evaluation, safety red teaming, bias and compliance audits.

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Data Product

Multimodal AI Data

Image-text data, video understanding, document AI, and cross-modal alignment at production quality.

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Data Product

Frontier Alignment

CoT reasoning, SME RLHF, SFT demonstrations, DPO data, and red teaming for frontier model post-training.

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Workflow

How the program runs.

01Guideline Design
02Rater Calibration
03Production Rating
04QA Sampling
05Evaluation
06Continuous Iteration

Continuous loop — outputs feed back into the data engine.

Quality & compliance

Built for regulated, high-stakes work.

Every engagement runs on our quality system and enterprise-grade security workflows — the controls an auditor would expect.

Secure rating workspaces
Policy version control
Quality audit trails
Data retention controls

Quality & Security model

Case study

Proof in production.

Foundation Models

Scaling Expert Reasoning Data for Frontier Model Alignment

Expert reasoning and preference data for domain-specific model alignment — 40+ qualified SMEs producing calibrated CoT and preference labels across STEM and finance.

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