Construction Draw Review with AI: Automating the Payment Application Workflow
AI can flag billing discrepancies, verify lien waiver compliance, and cross-check schedule of values before your inspector sets foot on site.
Construction draw review is one of the most document-intensive recurring tasks in development finance. For a project with monthly draw cycles and 30+ subcontractor line items, a single draw package can run hundreds of pages -- G702/G703 payment applications, lien waivers, sworn statements, inspector reports, cost-to-complete certifications. Most lenders and owners still review these manually.
AI is changing that. Not by replacing the inspector or the draw administrator, but by compressing the pre-review work that currently takes days into hours.
What a Draw Review Actually Involves
Before a development lender or owner approves a payment application, the review covers several distinct checks:
Schedule of values verification. Does the contractor's reported percent-complete on each line item align with the updated schedule of values? Are there line items that appear front-loaded -- designed to capture profit early rather than reflect actual work in place?
Lien waiver compliance. Has every subcontractor and supplier submitted conditional lien waivers for the current draw and unconditional waivers for the prior draw? Are any missing? Any waivers that cover a different dollar amount than the payment application?
Cost-to-complete cross-check. Does the draw request, combined with prior approved draws, leave sufficient budget to complete each scope? Has any line item consumed more than its allocated share before the work is reasonably complete?
Inspector report alignment. Do the contractor's reported completion percentages align with what the third-party inspector observed on site? Significant deviations -- a contractor claiming 70% complete on structural steel while the inspector logged 55% -- are a common source of over-draw.
Retainage tracking. Is retainage being withheld at the correct rate? Has retainage been released on any line items prematurely?
What AI Can Handle
Modern document AI can execute most of the above in a single pass through the draw package:
Cross-document extraction. AI can extract every line-item figure from the G702/G703, map it to the approved schedule of values, and flag any variance that exceeds a defined threshold -- typically 5-10% on individual line items, or any front-loading pattern that suggests profit-pulling.
Lien waiver reconciliation. If lien waivers are submitted as PDFs, AI can extract the counterparty name, amount covered, and waiver type (conditional vs. unconditional), then cross-check against the payment application's subcontractor list. Missing waivers and amount mismatches are flagged automatically.
Inspector report comparison. AI can ingest both the payment application and the inspector's field report and produce a line-by-line variance table -- percent-complete as claimed vs. percent-complete as observed. Deviations above the threshold go to a human reviewer for judgment.
Retainage audit. AI can track cumulative retainage held vs. the contractual requirement and flag any early-release or under-withholding.
What AI Cannot Do
Site judgment. Whether the inspector's reported completion is itself accurate requires physical presence and construction expertise. AI can flag that the inspector and contractor disagree; it cannot adjudicate who is right.
Intent assessment. A front-loaded schedule of values may reflect GC profit optimization, aggressive billing, or cash flow pressure. Identifying which requires a conversation, not a document.
Lien priority analysis. Complex lien situations -- where a supplier disputes the waiver amount or a subcontractor is partially in default -- require legal judgment that sits outside AI's current capability.
Approval authority. Draw approval carries liability. A human draw administrator or lender representative must review the AI output and sign off. AI produces the analysis; humans make the decision.
Deployment Patterns
The most effective deployment model is AI as a first-pass filter, not a replacement reviewer. The draw package comes in, AI runs the full cross-document check and produces a flagged summary: line items to review, missing waivers, inspector variances, retainage discrepancies. The draw administrator reviews flagged items only, rather than the full package.
On a 40-line-item draw with no major issues, this compresses a 4-6 hour manual review to under an hour. On a draw with multiple discrepancies, the AI output directs the reviewer exactly where to spend time.
Teams using Hebbia, FifthDimension, or Build for document-intensive workflows have applied similar approaches to draw management. The setup investment -- document templates, variance thresholds, lien waiver format libraries -- typically pays back within the first draw cycle.
The Bottleneck It Solves
Draw review delays cost money. A lender holding a draw for 10 additional days while reviewers work through a 400-page package directly increases a developer's carry cost. On a $100M construction loan at 7%, a 10-day delay is roughly $190,000 in additional interest carry. Compressing that cycle is not a marginal efficiency gain -- it is a real line item on the project budget.
The draw review use case is also a clean proof-of-concept for AI in development operations more broadly. The inputs are structured (standard AIA forms), the rules are well-defined (lien waiver requirements, retainage rates), and the output is reviewable by a human with domain expertise. It is one of the lower-risk entry points for AI in a development workflow, and one of the higher-value ones.