Solutions · LLM training data

Expert data for fine-tuning and aligning LLMs

Prompt–response pairs for supervised fine-tuning, ranked outputs for RLHF, and expert review — including low-resource languages and proprietary coding languages with no public training data.

A man seen from behind in a bright office, reading text on a laptop and marking a printed rubric with a pen

The problem

Why this is hard to do well

01

No talent pool

Low-resource and proprietary languages have few people who can write or judge them.

02

Ranking, not labeling

Alignment needs prompts matched to outputs and candidates ranked by correctness, not single labels.

03

Plausible isn't correct

LLM output reads well even when it's wrong, so reviewers have to be real experts.

How MLtwist does it

Platform and people, together

Our platform does the repeatable work; our team, yours, or both handle the judgment calls. Every version ships with a Data ID Card.

Supervised fine-tuning data
Prompts written to match target outputs, in the style and format your model needs.
Preference ranking for RLHF
Candidate outputs ranked by correctness, with the reasoning recorded.
Sourced and tested experts
Coders, linguists, and domain specialists recruited and skill-tested before they touch data.
Agreement scoring
Multi-stage review and inter-annotator agreement on every pair.

Talk to us about llm training data

Tell us the data type, volume, and timeline. We'll scope it with our team, yours, or both — and deliver it versioned, in your format.

Also available through Carahsoft and Google Cloud Marketplace.