QA from Docs Documents in.
Documents in.
QA datasets out.
Upload textbooks, manuals, or internal docs. Get back structured Q&A datasets with every answer cited to the source — ready for fine-tuning.
Minutes, not weeks
Hand us your internal docs and get back thousands of high-quality Q&A pairs the same day. Go from idea to fine-tuning in a single sprint.
Cross-checked and citable
Every answer is verified against the source and traceable back to the original text. No hallucinated labels.
Any messy source
PDFs, transcripts, manuals, internal docs. We handle the chunking, question generation, and labeling — you get a dataset ready for fine-tuning.
Simple, powerful API
Upload your documents and get verified Q&A datasets in minutes.
- Every answer cited back to the original source text
- Cross-checked for accuracy — no hallucinated labels
- Export as HuggingFace, Parquet, or JSON
from lightningrod import Pipeline
pipeline = Pipeline([
FileSetSeedGenerator(file_set_id="your-fileset-id"),
QuestionAndLabelGenerator(
questions_per_seed=3,
instructions="Questions that test deep understanding"
)
])
dataset = pipeline.run(n_samples=100) Trusted by teams building AI