How do I turn concrete delivery ticket photos into a pour log with ordered versus delivered yards and ticket-time flags using AI?
After a big pour, the tickets end up in a truck door pocket, and the questions come later: how many yards actually went into that placement, which loads had water added on site, which trucks sat too long before discharge, and does the supplier's invoice match. Photograph every delivery ticket as the truck arrives, have Claude or ChatGPT read the photos into a log, and have Copilot in Excel or Gemini in Google Sheets total delivered yards per placement against what was ordered and flag loads outside the limits you type from your own project specification. Acceptance of the concrete, and anything the testing agency or engineer must rule on, stays with them.
Superintendent · Construction · Claude · ChatGPT · Microsoft Excel · Microsoft Copilot · Google Sheets
Content updated · Tool links listed below; vendor features and pricing change, so confirm with the vendor
Short answer
Use Claude or ChatGPT, then Copilot in Excel or Gemini in Google Sheets: Claude or ChatGPT reads photos of concrete delivery tickets into a log (mix ID, yards, batch, arrival and discharge times, water added as written); Copilot or Gemini totals delivered yards per placement against ordered and estimated yards and flags loads outside the limits you typed from your own specification. After a big pour, the tickets end up in a truck door pocket, and the questions come later: how many yards actually went into that placement, which loads had water added on site, which trucks sat too long before discharge, and does the supplier's invoice match. Photograph every delivery ticket as the truck arrives, have Claude or ChatGPT read the photos into a log, and have Copilot in Excel or Gemini in Google Sheets total delivered yards per placement against what was ordered and flag loads outside the limits you type from your own project specification. Acceptance of the concrete, and anything the testing agency or engineer must rule on, stays with them. A person still checks: every flagged load and any rejection with the testing agency and engineer of record, and the yard totals against the supplier's invoice before approval.
AI tie-in
Tool: Claude or ChatGPT, then Copilot in Excel or Gemini in Google Sheets
Claude or ChatGPT reads photos of concrete delivery tickets into a log (mix ID, yards, batch, arrival and discharge times, water added as written); Copilot or Gemini totals delivered yards per placement against ordered and estimated yards and flags loads outside the limits you typed from your own specification.
Prompt 1
Read these concrete delivery ticket photos [upload]. Build a table with one row per ticket: ticket number, truck, mix ID, yards this load, cumulative yards, batch time, arrival, discharge start and finish, water added as written, remarks. Copy values exactly. Write UNREADABLE or NOT SHOWN instead of guessing. Do not judge whether a load was acceptable.
Prompt 2
Here are the headers and a few sample rows of my Tickets tab [paste] and Placements tab [paste]. Settings!B1 is the maximum batch-to-discharge time and Settings!B2 the water-added limit I typed from my project specification. Write Excel formulas (or a step-by-step Copilot plan) that total delivered yards per placement against ordered and estimated yards, and flag loads with a mix ID not approved for that placement, time over B1, water over B2 or missing times. Use only my values; do not supply limits from memory.
Human check: Every flagged load and any rejection with the testing agency and engineer of record, and the yard totals against the supplier's invoice before approval.
The problem
Turn concrete delivery ticket photos into a pour log with ordered versus delivered yards and ticket-time flags using AI. This is a common, time-consuming task for a superintendent.
What this workflow does
After a big pour, the tickets end up in a truck door pocket, and the questions come later: how many yards actually went into that placement, which loads had water added on site, which trucks sat too long before discharge, and does the supplier's invoice match. Photograph every delivery ticket as the truck arrives, have Claude or ChatGPT read the photos into a log, and have Copilot in Excel or Gemini in Google Sheets total delivered yards per placement against what was ordered and flag loads outside the limits you type from your own project specification. Acceptance of the concrete, and anything the testing agency or engineer must rule on, stays with them.
How it works: AI drafts or analyzes. A person operates the tools, checks the work, and takes action.
Your checkpoint: The log shows what the tickets say and which loads fall outside the limits you typed. It does not accept or reject concrete, judge strength or durability, or replace the testing agency's field records. Rejected loads, anything about water added, and acceptance of the placement stay with the superintendent, the testing agency and the engineer of record.
Before you start
- Access to the named tool; confirm license, version and cost with the vendor.
- A small, non-confidential sample to try the workflow on first.
- A qualified person to review the output before it is used.
Tools and access
Follow the steps
- Before the pour, type into a Settings tab the limits from your own project specification and approved mix submittal, in your own words: the maximum time from batching to discharge, whether water may be added on site and how much, and the approved mix IDs for each placement. Don't take these from memory or from the AI.
- Set up a Placements tab: placement ID (for example the pour area and date), approved mix ID, ordered yards and the estimated neat quantity from takeoff.
- Photograph each ticket at the truck, front and back if anything is handwritten, including the batch time, the arrival and discharge times the driver or your crew writes on it, and any water-added note.
- After the pour, have Claude or ChatGPT read the photos into a Tickets tab: ticket number, truck, mix ID, yards on the load, cumulative yards, batch time, arrival time, discharge start and finish, water added as written and remarks. It copies values exactly and writes UNREADABLE or NOT SHOWN instead of guessing.
- Have Copilot in Excel or Gemini in Google Sheets total delivered yards per placement, compare them with ordered and estimated yards, and flag loads with a wrong mix ID, batch-to-discharge time over your limit, water added beyond what your spec allows, or missing times.
- Attach the log to the daily report, send the flags to the PM and the testing agency the same day, and reconcile the supplier's invoice against the Tickets tab before it is approved.
Try a small example
Replace the bracketed fields with your own project details. No tested sample run is published for this workflow yet.
Sample input
Fill in the bracketed [fields] in the text below with your project data.
Starter prompt
Read these concrete delivery ticket photos [upload]. Build a table with one row per ticket: ticket number, truck number, mix ID, yards this load, cumulative yards, batch time, arrival time, discharge start, discharge finish, water added as written and remarks. Copy every value exactly as printed or handwritten. Write UNREADABLE for anything you cannot read and NOT SHOWN for anything missing. Do not convert units, fill gaps or judge whether a load was acceptable.
Expected output
Not published yet. Treat any output as a draft and check it against the source documents.
Check the result
- Every value, citation or quantity traces back to a source document.
- Missing information is marked as missing, not filled in.
Limits and recovery
- The log shows what the tickets say and which loads fall outside the limits you typed. It does not accept or reject concrete, judge strength or durability, or replace the testing agency's field records. Rejected loads, anything about water added, and acceptance of the placement stay with the superintendent, the testing agency and the engineer of record.
- Check your organization’s data policy before sharing project files with third-party tools.
Stop or switch when: The source cannot be verified, permissions are missing, or the result contains unsupported facts.
Frequently asked questions
How does AI help with this?
Claude or ChatGPT, then Copilot in Excel or Gemini in Google Sheets: Claude or ChatGPT reads photos of concrete delivery tickets into a log (mix ID, yards, batch, arrival and discharge times, water added as written); Copilot or Gemini totals delivered yards per placement against ordered and estimated yards and flags loads outside the limits you typed from your own specification. A person still checks: Every flagged load and any rejection with the testing agency and engineer of record, and the yard totals against the supplier's invoice before approval.
How do I how do I turn concrete delivery ticket photos into a pour log with ordered versus delivered yards and ticket-time flags using AI??
Before the pour, type into a Settings tab the limits from your own project specification and approved mix submittal, in your own words: the maximum time from batching to discharge, whether water may be added on site and how much, and the approved mix IDs for each placement. Don't take these from memory or from the AI. Set up a Placements tab: placement ID (for example the pour area and date), approved mix ID, ordered yards and the estimated neat quantity from takeoff. Photograph each ticket at the truck, front and back if anything is handwritten, including the batch time, the arrival and discharge times the driver or your crew writes on it, and any water-added note. The full step list is above.
Does this use an AI agent or regular software?
It is labeled AI assists: AI drafts or analyzes. A person operates the tools, checks the work, and takes action.
What tools do I need?
Claude, ChatGPT, Microsoft Excel, Microsoft Copilot, Google Sheets. Confirm license, version and cost with the vendor, and try it on a small non-confidential sample first.
Has this workflow been tested?
Workflow guide · not independently tested. Written from vendor documentation and practitioner use. Labels apply to the steps described here, not every feature of a product. Links were checked when the page was written.
Evidence and maintenance
Written from vendor documentation and practitioner use. Labels apply to the steps described here, not every feature of a product. Links were checked when the page was written.