Training data from
the real world
Your models are only as good as your data. Acquire structured training datasets from visual interfaces, dynamic web apps, and sources that traditional tools can't reach.
Data pipelines for ML teams
Build reliable data pipelines that feed your models with fresh, structured data from any source.
Training Dataset Generation
Acquire labeled datasets from visual interfaces. Product catalogs, pricing tables, user reviews—structured and ready for training.
RAG Knowledge Bases
Build retrieval-augmented generation datasets. Acquire documentation, support articles, and domain knowledge at scale.
Model Validation Data
Fresh real-world data for testing and validating your models against production conditions.
Fine-tuning Datasets
Domain-specific data for fine-tuning foundation models. Acquire industry-specific content formatted for training.
Benchmark Datasets
Build custom benchmarks from real-world sources. Compare model performance against production data.
Data Enrichment
Augment your existing datasets with additional features and attributes from external sources.
Built for ML engineers
We know the pain of data collection. Brittle pipelines, rate limits, format inconsistencies. Warpstack handles the data acquisition so you can focus on the models.
Output as JSON via API with SQL-like filters, or export to CSV. Schema validation built in. Incremental updates for keeping datasets fresh.
Your data pipeline, handled
Stop writing brittle scrapers. Get structured, validated data for your ML workflows.