Describe the dataset you need in plain English. RasoSynthTune discovers sources, extracts content, enforces quality, runs human review, and exports production-ready fine-tuning data — fully autonomously.
From natural-language description to fine-tuning-ready dataset in 6 stages
Natural Language
Describe your dataset
Source Discovery
Find relevant content
Content Extraction
Chunk & parse sources
Quality Filters
toxicity • dedup • schema
Human Review
Approve / reject samples
Fine-tuning Dataset
JSONL · ShareGPT · Alpaca
Hover a stage to learn more
Describe what you want in plain English. RasoSynthTune orchestrates the full pipeline, from source discovery to human review, automatically.
LangGraph-powered multi-stage pipeline with checkpointing, provider failover, and graceful degradation when APIs fail.
Every sample can be approved or rejected by a human judge before it enters your fine-tuning set. No more bad data silently polluting your model.
Download in JSONL, ShareGPT, Alpaca, or OpenAI fine-tuning format. Ready to upload to any trainingInfrastructure.
Pipeline Stages
6
analyze → export
Export Formats
4
JSONL · ShareGPT · Alpaca · OpenAI
Dataset Types
12
SFT · RAG · RLHF · reasoning…
Human Review
Yes
approve / reject every sample
Go to the Studio, describe what you need, and watch the pipeline run end-to-end.