The Dharma Field Extractor uses a 2-billion-parameter architecture to pull targeted information from complex document types into clean JSON structures. Organizations can implement the system in an open discovery format or restrict parsing to a predefined schema featuring strict typing rules. To handle these multi-domain extraction tasks across varied international formats, developers trained an adapter using tens of thousands of bilingual samples.
Key points
Enterprise pipelines can automatically parse high-volume records like identification card…: Enterprise pipelines can automatically parse high-volume records like identification cards and medical requisitions without per-document fine-tuning.
Schema-directed mode enforces exact target data types such as booleans and populates tabl…: Schema-directed mode enforces exact target data types such as booleans and populates table rows while assigning null values to missing keys.
The specialized system outperforms tested general-purpose frontier large language models…: The specialized system outperforms tested general-purpose frontier large language models at lower latency and reduced operational costs.
Sources checked by our analysis pipeline: 1
A 2-billion-parameter model that extracts exactly the fields you ask for, from any document type, outperforming every frontier LLM we tested, at a fraction of the cost.
In April, we released DharmaOCR-LITE, a model specialized for OCR across a wide range of documents, from contracts and court filings to invoices, IDs and forms. The paper behind it made a narrow, well-measured case for domain specialization: a smaller model trained closer to its task beating general-purpose frontier APIs on that task.
OCR gives you the text on a page, faithful to the original formatting. That's exactly what you want when the job is the whole document, like a contract you'll read end to end or a manuscript you're digitizing.
However, there's a different use case: you don't want the page, you want specific fields out of it, in a shape a system downstream can consume. Every line item on an invoice, as a list. The patient name, exam type and date from a medical requisition, ready to schedule. The fields off an ID, mapped to the columns of an employee record.
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