I compared the four main ways to parse receipts programmatically.

Here's what I found — after actually using all of them, not just reading the docs.

𝗔𝗪𝗦 𝗧𝗲𝘅𝘁𝗿𝗮𝗰𝘁 𝗔𝗻𝗮𝗹𝘆𝘇𝗲𝗘𝘅𝗽𝗲𝗻𝘀𝗲 ✓ Enterprise-grade reliability ✓ Native AWS ecosystem ✗ Requires IAM role + S3 setup (1–2 hours before your first call) ✗ Output is deeply nested key-value blocks — you end up parsing the parser ✗ Accuracy drops on faded thermal paper and non-English receipts ✗ $0.01/page — costs scale linearly, no flat rate

𝗚𝗼𝗼𝗴𝗹𝗲 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗔𝗜 ✓ Google-grade infrastructure ✓ Better multilingual support than Textract ✗ GCP project + service account + processor selection required ✗ $65 per 1,000 pages for specialized processors ✗ No self-hosting — everything is sent to Google's servers

𝗩𝗲𝗿𝘆𝗳𝗶 ✓ Clean JSON output ✓ Receipt-specific with solid field coverage ✗ Pricing tier isn't indie-project friendly ✗ No self-hosting option

𝗥𝗲𝗰𝗲𝗶𝗽𝘁 𝗣𝗮𝗿𝘀𝗲𝗿 𝗔𝗣𝗜 (what I built) ✓ One HTTP call, structured JSON response, no setup ✓ 50+ fields including line items, payment method, tip ✓ Works on handwritten receipts and non-English documents ✓ Self-hosting available with your own Anthropic key ✓ Free tier — 5 calls/month, no credit card ✗ Not SOC 2 certified — not the right fit for regulated enterprise ✗ No batch processing yet

Bottom line:

→ Need enterprise compliance and you're already on AWS? Use Textract. → Need the fastest path from receipt photo to usable JSON in your app? Try the demo first.

Link to the live demo is in the first comment.

API #DeveloperTools #ReceiptParsing #OCR #AWS #Fintech #IndieDev #BuildInPublic