Fine-tuning data
Supervised samples organized for classification, extraction, summarization, and grounded QA workflows, suitable for domain adaptation and SFT.
We turn vertical public-source text into data products that can enter real AI workflows, instead of handing over a loose pile of documents. This page explains the three main product forms and the delivery standards they share.
Fine-tuning data · RAG corpora · Evaluation data · Shared delivery qualities
Supervised samples organized for classification, extraction, summarization, and grounded QA workflows, suitable for domain adaptation and SFT.
Structured corpora that preserve source links, passage boundaries, and metadata, making them easier to chunk, index, and trace inside knowledge systems.
Reusable validation sets that pair real questions, expected outputs, and cited evidence for regression testing and model comparison.
Across all product forms, we emphasize traceability, structural consistency, quality checks, and offline delivery that teams can adopt quickly.