Data foundry
Curate, label, audit.
Data is the part of the system that determines what your model knows. Our foundry curates, labels, versions, and audits training and prompt data — with the contracts and reviews that production AI requires.
Why data work is the underrated lever
Most model gains in the last three years have come from data quality, not parameter count. Curated training data, well-formed prompts, and clean feedback loops outperform clever model choices most weeks. The foundry is where we do that work — slow, deliberate, and reviewed.
What the foundry operates
Curation
Source vetting, deduplication, decontamination, and provenance tracking.
Labeling
Mixed human + LLM labeling pipelines with inter-rater calibration.
Synthetic data
Generated data for long-tail classes, with explicit quality gates.
Versioning
Reproducible training sets. Every model maps to a known data revision.
Audit trails
Every record's origin, license, and usage rights — queryable.
Feedback loops
Production traces routed back to labeling. Drift fed back to curation.