PROJECTS
generate-data.com
Synthetic test data for systems that fail on tidy demos.
generate-data.com is a synthetic test data platform for teams evaluating matching, scoring, and other intelligent systems. Unlike generic faker tools, you can configure quality characteristics such as exact duplicates, fuzzy duplicates, and realistic field-level variation, so test datasets look like the messy production inputs your models and pipelines will see. That makes regression suites and QA datasets honest about failure modes tidy unique rows would hide.
The problem it solves
Most synthetic generators invent clean, unique rows. Matching systems, quality scorers, and evaluation harnesses fail on duplicates, typos, and field-level drift. If your tests never inject that mess, they pass while production still breaks. generate-data treats input quality as configuration, not an afterthought script.
Key capabilities
- Schema modeling with configurable field types
- Adjustable data quality levels per field
- Exact and fuzzy duplicate injection with Master ID and Duplicate Type columns for record-linkage testing
- Export to CSV, JSON, XML, Parquet, JSONL, and HuggingFace dataset formats
- API access for programmatic data generation, with API keys
- AI-assisted schema generation, up to 1,000 AI-generated rows per batch (Premium)
- Catalog of free pre-built datasets
- Free and Premium tiers
Who it's for: Engineers and researchers testing matching and quality systems. QA teams building regression datasets for intelligent pipelines.