Pick a schema
Choose the document type — the target fields are fixed up front so output is predictable.
Live · NLP · LLM
Structured extraction
Turn messy, unstructured text into clean structured data. Pick a document type, paste (or edit) the text, and the LLM extracts the fields into JSON — grammar-constrained so the output is always valid, never a broken half-response.
Document type
Runs a local LLM on CPU — expect 8–20 s. Output is grammar-constrained to valid JSON.
Extracted JSON
Fields () will appear here as clean JSON.
How it works
Prompt
The model is asked to extract exactly those fields, using null for anything missing.
Grammar constraint
A GBNF grammar forces the model to emit valid JSON — no markdown, no trailing prose.
Coerce to schema
The result is mapped onto the fixed field set so the UI is always stable.
Local model
Qwen2.5-1.5B on CPU. Small but reliable for bounded extraction tasks like this.
Production swap
Add confidence scoring, validation rules, and Claude/GPT for tougher documents — same contract.
Extracting from your own documents?
We build production extraction for contracts, invoices, claims, and forms — with confidence scores, human-in-the-loop review for low-confidence fields, and validation against your systems of record.
Ready to start
Turn one AI use case into measurable production value.
Book a 30-minute consultation. We will walk through the use case, sketch the value case, and tell you honestly whether we can help.