Claims Intake Automation: Photos/PDFs → Google Sheets in One Workflow

Claims intake is often where delays start: someone emails a photo of a damaged item, another person forwards a PDF report, someone else retypes everything into a spreadsheet, and errors sneak in along the way.

Img2Sheet helps you turn that messy intake into a repeatable workflow: define the exact fields you need once, then upload photos/PDFs and automatically extract structured claim data into Google Sheets in the same column order—every time.

And because we use AI extraction (not just OCR), you’re not limited to “text recognition.” You can instruct the system what to capture and how to format it—even when the document layout changes.

The problem with traditional OCR in claims intake

Basic OCR is good at reading characters. But claims intake usually requires more than reading:

  • Understanding which number is the policy number vs a reference number
  • Capturing dates correctly (loss date vs report date)
  • Extracting values that aren’t in neat tables
  • Producing consistent output even when forms, photos, and PDFs vary

That’s where AI extraction helps: it’s designed to interpret context, not only recognize text.

How Img2Sheet works (the “structure-first” approach)

Instead of trying to guess what you want from every upload, you start by creating a Structure:

Each column is defined by:

  • Label (what the column is called in your sheet)
  • Type (text or number)
  • Prompt (a precise instruction describing what to extract)

Then you upload a photo/PDF for that structure. The extracted data is inserted into Google Sheets matching your structure’s columns.

This gives you predictable, clean rows ready for:

  • triage
  • assignment
  • fraud checks
  • reserve estimation
  • reporting dashboards

Example: A claims intake Structure you can copy

Here’s a practical column set for many claim types (auto/property/general):

  1. Claim ID (text) — “Extract the claim number/reference if present.”
  2. Policy Number (text) — “Extract the policy number. Ignore other IDs.”
  3. Insured Full Name (text) — “Full name of the insured person.”
  4. Phone (text) — “Phone number of insured/contact.”
  5. Email (text) — “Email address of insured/contact.”
  6. Loss Date (text) — “Date of incident/loss. If multiple dates, choose loss date.”
  7. Report Date (text) — “Date the claim was reported/created.”
  8. Loss Location (text) — “Address or location of the incident.”
  9. Claim Type (text) — “Auto / Property / Liability / Other (infer from document if needed).”
  10. Damage Summary (text) — “Short summary of damage described.”
  11. Estimated Amount (number) — “Total estimated amount/repair cost if present.”
  12. Currency (text) — “Currency code or symbol (e.g., USD, EUR, MAD).”
  13. Third Party Involved (text) — “Yes/No + short detail if mentioned.”
  14. Police Report Number (text) — “Police report ID if present.”
  15. Adjuster/Agent Notes (text) — “Any notes/comments section content.”

You can tailor this to your workflow (e.g., add vehicle VIN, plate number, contractor name, bank details, etc.).

One workflow, multiple intake sources

You can use the same structure for:

  • Photos taken in the field (damage, forms, IDs)
  • Scanned PDFs (police reports, invoices, medical receipts)
  • Email attachments exported to a folder
  • Multi-page claim packets

Because the structure defines the output, your Google Sheet stays consistent even when inputs vary.

Privacy & data handling

Two important points:

  • No file link is stored or shared: uploads aren’t kept as downloadable links.
  • Files are removed immediately after extraction: once extraction is completed, the source file is deleted.

That means you keep your intake fast without building a storage backlog of sensitive documents.

Setting prompts that improve accuracy (quick tips)

To get clean, dependable rows, prompts should be explicit:

  • Specify which date: “loss date” vs “report date”
  • Specify exclusions: “ignore invoice number and reference IDs”
  • Specify formatting: “return only digits,” “return as a number,” “exclude currency symbol”
  • Define fallback behavior: “If missing, return blank”

Example prompt upgrade

  • Weak: “Extract total”
  • Strong: “Extract the final payable total amount. Exclude tax breakdown lines. Return a number only.”

What you unlock once claims are in Sheets

Once every claim becomes a standardized row, you can:

  • route claims by type/region
  • auto-assign to adjusters
  • flag missing data instantly
  • build real-time dashboards
  • export to your TPA/core system later (CSV/API automation)

In other words: Sheets becomes your intake hub, not a manual data-entry graveyard.

Wrap-up

Claims intake doesn’t need to be slow or messy. With a structure-first approach powered by AI extraction, you can turn photos and PDFs into clean Google Sheets rows—consistently, securely, and at scale.