An AI agent that builds production-ready datasets from scratch. Synthetic generation, RL data, feature engineering — just describe what you need.
Building your dataset...
From idea to production-ready dataset in three simple steps
Tell Vero what dataset you need — schema, domain, size, labels. It understands any data task.
Vero searches providers, generates synthetic data, combines sources, and engineers features automatically.
Receive a clean, validated dataset ready for training. Ask follow-ups to refine and iterate.
Vero searches across providers, generates synthetic data with SAM, LLMs, and other models, then combines and engineers features to build the perfect dataset for your task.
Use SAM, LLMs, diffusion models, and other AI to generate synthetic data at scale. Build RL datasets for LLM finetuning, create labeled examples, and augment real-world data — all from natural language.
Prompt Generation
LLM generates diverse prompts & completions
Preference Pairs
Building chosen/rejected pairs for DPO
Validation & Export
Quality checks and HuggingFace upload
From RL finetuning data to annotated images, Vero builds it all
Build DPO, RLHF, and reward model datasets with LLM-generated preference pairs and human feedback schemas.
Generate labeled NLP datasets at scale — classification, NER, sentiment, QA — using LLMs as annotators.
Auto-label images with SAM, CLIP, and vision models. Segmentation masks, bounding boxes, and captions.
Search HuggingFace, Kaggle, and other providers. Combine, deduplicate, and merge into unified datasets.
Automated feature creation, type conversion, encoding, and statistical analysis on any tabular data.
Chain any combination of generation, transformation, and validation steps for your specific domain.
Join the waitlist for early access. Be among the first to build production-quality datasets with AI.