Your AI is only as good as its data.
In 30 minutes you'll build the pipeline that turns messy real-world documents into clean, structured AI fuel.
It starts with choosing a messy document.
Real data is ugly. PDFs with tables. HTML with ads. CSVs with missing fields. Scanned images.
Before your AI can learn anything, someone has to clean this up. That someone is your pipeline.
Click on a document type to see what goes wrong:
Pull text from anything. PDF parsing (layout-aware vs raw text), HTML to markdown, OCR for images, table extraction.
Extraction is 90% of the work and gets 10% of the attention.
Paste a URL or upload content to extract:
Raw text → clean chunks ready for embedding or training. Remove boilerplate, normalize whitespace, handle Unicode, split at natural boundaries.
The wrong chunk size is why your RAG doesn't work.
Apply different chunking strategies to see the results:
Split every N characters
Split at sentence boundaries
Split at paragraph breaks
Split by topic/meaning
For fine-tuning and eval, you need labeled data.
Labeling is boring. It's also the highest-leverage thing you can do for your AI.
Label 10 examples to see how annotation works:
Not enough real data? Generate it. Use a strong model to create training data for a smaller model.
The best AI companies all use synthetic data. The bad ones pretend they don't.
Write a generation prompt to create training examples:
Synthetic data can inherit biases and patterns from the generating model. Always validate against real-world examples and avoid training on your own model's outputs (model collapse).
// Contamination check
function checkContamination(syntheticData, trainingData) {
const similarities = syntheticData.map(synthetic =>
trainingData.map(real =>
calculateSimilarity(synthetic, real)
).max()
);
const highSimilarity = similarities.filter(sim => sim > 0.9);
return {
contaminationRate: highSimilarity.length / syntheticData.length,
flagged: highSimilarity.length > 0
};
}From messy documents to clean, labeled, AI-ready data.
This is the foundation every AI system needs.