Turn signed POD photos and scans into structured delivery fields your ops team can review, correct, and send to Sheets or a webhook. Turn signed POD photos and scans into structured delivery fields your ops team can review, correct, and send to Sheets or a webhook.
Create your first parser in minutes. No code, no setup calls.
Normalize new-hire PDFs into structured fields, review before HRIS entry, and limit contractor access to the parsers you assign in Parsedit.
Proof-of-delivery files are rarely tidy PDFs. Drivers snap a clipboard in a doorway, upload from a phone, and ops inherits glare, thumbs, and cropped signature blocks. Storing images in Drive answers “do we have a file?” It does not answer “who signed, when, for which reference?”
Document extraction with OCR and a short schema turns POD images into rows. Review stays mandatory for blurry captures.
POD photo to structured fields.
Keep the parser thin:
Skip decorative letterhead fields. Schema discipline: Design invoice parser schema principles apply equally here.
OCR runs automatically on photos and scans. Document intake.
Expect more touches than clean AP PDFs. Use PDF/image text selection when reference numbers are readable but missed. Reject or re-request captures that cannot support a dispute. Review with text selection.
Multi-stop packets in one PDF should split into children when types/segments differ. Packets.
Native QuickBooks/Xero matter less here unless POD triggers billing documents you also extract.
Parsedit is the extraction and review lane for POD files feeding tools you already run. Soft CTA: pilot one lane or customer with the worst photo quality first. Related: Document workflows to automate.
A POD row without a retrievable image is weak evidence. Keep the source file in Parsedit history (and in your TMS if you attach outbound). When a customer disputes delivery, open the child or document and verify the capture quality before arguing from the structured fields alone.
Pilot one lane, one depot, or one customer with chronic POD chaos. Measure:
Fix intake instructions (closer photo, include reference label in frame) before you automate send.
Whatever you put in reference_number must match the TMS key ops uses in search. If drivers photograph only the signature page without the PRO label, extraction cannot invent it. Update driver instructions before you blame the parser.
Drivers upload to a shared Drive folder nightly. Ops imports each morning.
PODs are an ops data problem first. Treat photo quality as part of the pipeline design, not an afterthought for the model.
When reshoot requests become common on a lane, fix the physical process (better lighting poster at the dock, label placement) before buying a “better OCR” story. The camera angle is part of your schema’s success rate.
Proof of delivery OCR, POD data capture, and delivery scan to spreadsheet are high-intent ops searches. Stress reference numbers and reshoot rules.
Handwritten signatures as data? Capture recipient name fields when printed; treat signatures as image evidence in the stored file.
Mobile app required? No. Email and Drive cover many fleets.
How do credits work for photos? Image pages still consume page credits per processed page counts as billed.
Create a POD parser, import last week’s worst photos, measure review time. Start free.
