Minutes per invoice processed
The direct labor cost and the clearest before-and-after number.
Construction and general contractors · Document intake and data extraction
Less retyping between jobsite paperwork and your systems
A busy general contractor processes hundreds of documents a month: subcontractor pay applications, supplier invoices, delivery tickets, conditional and unconditional lien waivers, change order requests, certificates of insurance. Most arrive by email as PDFs or phone photos, and an AP clerk or project coordinator keys the important fields into Procore, Sage 100 Contractor or QuickBooks by hand.
How it often works today
- AP staff open each supplier invoice, look up the job and cost code, and key it into accounting, often several hundred invoices a month.
- Lien waivers are matched to payments by hand, so a missing conditional waiver may not surface until the owner's draw is held.
- Delivery tickets are photographed in the field and texted to the office, then compared to invoices only when a quantity looks obviously wrong.
- Sub pay applications are checked against the schedule of values line by line in Excel before they can roll into the owner's AIA G702/G703.
Document extraction tools and AI models now read these forms reasonably well, as long as a person checks the results. A scoped project would route incoming documents to one inbox, extract fields such as vendor, job number, cost code, amount and retainage, match them to commitments, and queue them for a human to approve before anything posts.
The improved workflow
One intake inbox
Vendors, subs and field staff send documents to a single address or upload folder per document type, so nothing waits in a PM's personal inbox.
Classify and extract
An extraction step identifies the document type and pulls the fields that matter: vendor, invoice number, job, cost code, amount, retainage, waiver type and through date.
Match to what you expected
Invoices are matched to purchase orders and subcontract commitments in Procore or accounting, and mismatches above a set tolerance are flagged for review.
Human approval queue
AP or the PM checks each extracted record against the original, approves or corrects it, and only then does it post. Corrections are tracked by vendor to spot problem formats.
Close the loop on waivers
Payments without a matching waiver are listed weekly so the coordinator can chase them before the next draw is submitted.
How we deliver this: AI automation for small business or fractional CTO leadership, scoped in writing and run over 90 days. See pricing or the sample scope.
What we would measure
Correction rate on extracted fields
Shows whether extraction can be trusted and which vendors' formats cause trouble.
Invoices processed within five days of receipt
Faster processing protects early-pay discounts and sub relationships.
Draws delayed by missing waivers
The expensive failure this work is designed to prevent.
Where people stay in control
- No invoice or payment posts until a person has approved the extracted record against the source document.
- Waiver types and through dates are verified by a person, since the legal effect of conditional and unconditional waivers differs.
- Bank details on vendor documents are never updated automatically; changes are confirmed by phone with a known contact to guard against payment fraud.
Example
Illustrative: month-end at a 25-person GC
For example, an AP coordinator handles around 400 supplier invoices and 60 sub pay apps a month across 12 jobs. With extraction and matching in place, most invoices arrive pre-coded, and the coordinator's time goes to the 15 or 20 flagged as mismatched. The weekly waiver report shows three subs paid without a conditional waiver on file, which gets fixed before the owner draw. Volumes here are illustrative.
Tools typically involved
What the first 30 days look like
We would pull a month of incoming documents, sort them by type and volume, and time how long AP and coordinators spend on each. The pilot usually starts with the highest-volume type, often supplier invoices, with a target for minutes per document and an acceptable correction rate.
Common questions
How accurate is AI extraction on construction documents?
It varies by document. Typed invoices from large suppliers extract well. Handwritten delivery tickets and blurry phone photos do not. We would test on a sample of your real documents and set the review process around the measured accuracy, rather than a vendor's claims.
Does Procore or Sage already do this?
Both have invoice capture options or partner add-ons, depending on your subscription, and turning on a feature you already pay for is often the cheapest fix. We would check what your current plans include before recommending another tool.
Can it build our pay application?
It can prepare the data: sub pay apps rolled up by line item, retainage calculated, waivers checked off. The controller or PM still reviews and certifies the owner's pay application before it is submitted, because that signature carries real responsibility.
The business case
Does it pay for itself?
Illustrative defaults for a general contractor. Replace them with your numbers.
What this workflow costs today
a month in staff time, before any lost sales
Monthly fee + assumed tools +
Break-even: new clients a month (at first-year value)
Or: staff hours recovered and redeployed
Break-even additional revenue
Value of +1 point of win rate
First 90 days, service fee
Worth a closer lookTest the assumptions
Illustration only, not a forecast or guarantee. Recovered staff time becomes a cash saving only if spending actually declines or the time goes into paid work. Tool costs are an assumption; we replace every number here with yours before recommending a scope.
Document intake and data extraction in other industries
Accounting and CPA firmsArchitecture firmsDental practicesElectrical contractorsEngineering firmsInsurance agenciesLaw firmsLogistics and freight companies
Document intake and data extraction: full guide
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