receipt-ocr alternatives
Curated alternatives to receipt-ocr — and why you'd switch.
contextgem
Declarative LLM extraction from documents: describe Aspects and Concepts in plain language, get structured values back with paragraph- or sentence-level references and built-in justifications.
Why switchSame idea — describe the fields, get structured values back. ContextGem is a general declarative extraction framework with paragraph-level references and justifications; receipt-ocr hardcodes one domain so there is nothing to design before it works.
Full comparison →chandra
Datalab's SOTA open OCR model: images/PDFs to structured HTML/Markdown/JSON with layout, tables, forms, checkboxes, handwriting and math, in 90+ languages. Local HF or vLLM inference.
Why switchBoth read an image and return structure. Chandra is a purpose-trained OCR model handling arbitrary layout, tables and handwriting; receipt-ocr just prompts a hosted VLM against a fixed receipt schema, which is cheaper to adopt and brittler off-domain.
Full comparison →unstract
LLM-driven platform turning unstructured documents into structured data: a no-code Prompt Studio to define extractions, then deploy as APIs or ETL pipelines. Self-hosted, AGPL + enterprise.
Why switchBoth turn documents into structured data with LLMs and expose an API. Unstract is a no-code platform with Prompt Studio, ETL deployment and enterprise licensing; receipt-ocr is a 50-line integration you can read in full.
Full comparison →