Foundation model data at scale
LLM Training Data
Instruction datasets, preference pairs, and evaluation benchmarks engineered for frontier language model performance.
Overview
What is LLM Training Data?
Training frontier language models requires carefully curated, diverse, high-quality datasets — instruction-response pairs, domain corpora, preference data, and evaluation benchmarks built to your data mix.
Why it matters: Model performance is increasingly a data problem, not a compute problem. The teams that win on quality, diversity, and domain coverage of training data build the models that actually ship.
Instruction Data
Diverse instruction-response pairs across 12+ expert domains
Preference Pairs
Ranked response pairs for DPO and RLHF-style fine-tuning
Eval Benchmarks
Custom evaluation sets aligned to your model's target capabilities
Bias & Safety Screening
Multi-pass review for factuality, bias, and toxicity
Workflow
How We Do It
01
Data Strategy
Define data mix, domain coverage, instruction types, and quality criteria aligned with your goals.
02
Expert Writing
Domain experts across 12+ disciplines craft diverse, accurate instruction-response pairs.
03
Quality Review
Senior reviewers validate factual accuracy, instruction clarity, and response quality.
04
Bias Review
Specialized reviewers screen for demographic, political, and factual bias across the dataset.
05
Delivery
Final datasets in JSONL with data cards, documentation, and quality metrics.
Case Study
Frontier AI Lab
Frontier AI Lab
Create 500K instruction pairs for frontier LLM fine-tuning
Solution
Expert writer network across 12 domains with multi-tier quality review
Results
500K
Instruction pairs
12
Domains covered
97%
Quality pass rate
Ready to Get Started with LLM Training Data?
Tell us about your project and we'll scope a pilot within 48 hours.