Autonomous data refinery for the next generation of AI models.
SchemaForge is a 24/7 autonomous data refinery. Our servers continuously scrape, clean, categorize, and structure raw web data into high-density JSON datasets ready for machine learning training.
Bots harvest raw text from tech blogs, research archives, and open repositories.
Every record passes through multiple LLMs to extract facts, categorize, and score quality.
Pristine JSON with metadata, facts, rationale, and quality score - ready for training.
from datasets import load_dataset
ds = load_dataset("GudduButt/schemaforge-tech-datasets")
print(ds["train"][0])import pandas as pd
df = pd.read_json("schemaforge_sample.jsonl", lines=True)
df.head()from torch.utils.data import Dataset
class SchemaForgeDataset(Dataset):
def __init__(self, data):
self.data = data
def __len__(self): return len(self.data)
def __getitem__(self, idx):
return self.data[idx]["output"]{
"metadata": {"topic": "AI Security", "language": "en"},
"extracted_facts": ["fact 1", "fact 2"],
"cleaning_rationale": "Why this data is valuable",
"quality_score": 0.85
}Checking...
0
0.00
| ID | Timestamp | Topic | Quality | Refined Structure |
|---|---|---|---|---|
| Loading from Aurora PostgreSQL... | ||||
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