About SchemaForge
We built the autonomous AI dataset refinery so researchers, engineers, and builders can stop cleaning data and start shipping models.
The Problem
Raw data is messy. Columns are inconsistent. Dates are in ten formats. Text fields contain noise. PII sneaks in. Most teams still spend more time cleaning than training.
Existing tools either require heavy coding or force you into rigid templates. We wanted something that understands your data, applies intelligent structure, and gives you production-ready output — automatically.
The Solution
SchemaForge is an autonomous AI pipeline. You upload raw files, choose an AI provider, optionally give instructions, and the system:
- Infers schema and cleans structure
- Standardizes formats and types
- Runs quality & consistency checks
- Produces downloadable or Hugging Face–ready datasets
Multiple frontier models (Gemini, Groq, Cerebras, SambaNova) power the refinement so you can pick the best fit for speed, quality, or cost.
Who it’s for
Researchers
Quickly turn scraped or experimental data into clean training sets.
ML Engineers
Skip the one-off cleaning scripts and get consistent, validated schemas.
Startups
Ship data products faster without hiring a full data engineering team.
Indie Builders
Prototype dataset pipelines with frontier AI in a few clicks.
Design Principles
AI-first, not template-first
The model adapts to your data instead of forcing you into fixed schemas.
Multi-provider by design
Choose the model that fits your latency, quality, or budget needs.
Production-ready output
Validation, schema inference, and export paths are built in — not afterthoughts.