Document Processing in Construction & Engineering
Construction and engineering firms process enormous volumes of documents on every project — bid packages, subcontracts, RFIs, submittals, shop drawings, change orders, pay applications, lien waivers, inspection reports, and certified payroll records, the list goes on.
Slow document review delays payment cycles and creates disputes that stall projects and erode margins.
LandingAI transforms documents into highly accurate, verifiable, structured data so teams can reliably automate document-intensive workflows.
Why Agentic Document Extraction for
Construction & Engineering
Faster Project Financial Cycles
Automating extraction from pay applications, change orders, and subcontractor invoices compresses billing review cycles and gets project teams paid without the delays that accumulate into cash flow problems.
Audit-Ready Compliance Documentation
Every extracted value is grounded to its precise location in the source document, giving project owners, general contractors, and public agencies a complete, traceable record across lien waivers, certified payroll reports, and safety documentation.
Scale Across Complex Project Portfolios
A single extraction pipeline handles the full document variety across active projects — drawings, contracts, field reports, and submittals — without requiring templates or custom configuration for each project type.
Built for Complex Construction & Engineering Documents
Intelligent document processing across general contracting, specialty subcontracting, civil and infrastructure engineering, and architecture and design is extremely difficult due to the sheer diversity of document types, the inconsistent layouts and the domain expertise required. Then add multiple languages, handwriting, photographs, scans and faxes to the complexity.
Accurate parsing of dense tables that span multiple pages and contain merged cells.
Single pipeline for image, slide, document, and spreadsheet file types with 1000+ pages.
Strong recognition of character-based languages, handwriting, checkboxes, stamps and signatures.
Schema-driven field extraction with visual grounding traceable to the original document.
Use cases
Pay Application Review
Extract line-item billing data, stored material amounts, and completion percentages from AIA G702/G703 pay applications, schedule of values, and subcontractor invoices to accelerate owner and GC approval cycles.
Shorten billing cycle approval time and improve project cash flow
Reduce manual data entry into cost management and ERP systems
Surface billing discrepancies and overbilling before approval
Submittal & RFI Processing
Extract, classify, and route specification data from submittals, shop drawings, product data sheets, and RFI logs so project teams can review and respond without manual transcription.
Accelerate submittal review cycles to keep construction schedules on track
Cut the administrative labor required to log, index, and distribute project submittals
Maintain a complete, traceable record of design clarifications and field decisions
Subcontractor Compliance & Lien Management
Extract and verify required data fields from lien waivers, certified payroll reports, insurance certificates, and subcontractor affidavits to confirm compliance before releasing payment.
Accelerate retainage release and final payment by completing compliance packages faster
Cut hours spent manually reviewing and reconciling lien waiver and certified payroll packages
Produce a defensible audit trail for public works prevailing wage and lien exposure requirements
Trusted for Document-Heavy Construction & Engineering Workflows
Agentic Document Extraction enables construction and engineering firms to automate document-intensive processes that traditionally require manual review.
Very often a loan officer who gets a borrower a solid preapproval fastest earns the deal and the real estate agent’s referrals. Reconstructing income is the hardest part, and Agentic Document Extraction is the cornerstone to getting it right and traceable. Accurate data upfront means we can get a cleaner loan file to the underwriter and get to CTC faster. Get it wrong and everything downstream gets affected.”
View case study →
Agentic Document Extraction has proven to be both accurate and easy to use. We are building on that foundation to deliver reliable, transparent, and scalable automation that our customers can validate and trust.”
View case study →
Trust is the product. Accuracy alone isn’t enough at enterprise scale—what matters is provenance, traceability, and control. LandingAI gives us confidence that every extracted value can be traced back to its source, audited, and defended. That’s what makes it deployable in regulated, real-world environments.”
View case study →Our Plan Review Agent has a lot of complicated components under the hood: traversing building code knowledge graphs, reasoning across disciplines and sheets, assessing issues informed by historical projects. None of it works if we can’t trust what came off the page. ADE gave us a reliable foundation, so our team could focus on incorporating our team’s expertise into our compliance reasoning system.”
View case study →
ADE has significantly outperformed other document extractors we’ve used. It has helped us build an Agentic RAG answer engine, based on unique healthcare institutional content, to offer instant, validated support to medical professionals at the point of care.”
View case study →
I appreciate its reliability and the fact that they're constantly innovating with new models, which helps us work smarter. The service is essential for handling heavy workloads in financial institutions as it provides the necessary infrastructure for high accuracy and fast throughput. I also find it adaptable to specific use cases because they're always working on new models.”
We use LandingAI's Agentic Document Extraction to build pipelines that turn unstructured text into structured data. First, the NER (Named Entity Recognition) detection has amazing accuracy. Second, the OCR capability is excellent — earlier I had to run a separate PDF extractor for text plus a separate LLM with OCR to summarize images, and now it's one step. Third, the image boundary detection is a standout.”
We ran a structured bake-off: the same five PDFs (ranging from a 12-page slide deck to a 400-page machinery manual) processed through other products and Landing AI's Agentic Document Extraction (ADE). We scored each tool on four criteria: Table fidelity, Figure extraction, Chunk typing, Scale. Landing AI ADE was the only tool that scored well on all four.”
Very often a loan officer who gets a borrower a solid preapproval fastest earns the deal and the real estate agent’s referrals. Reconstructing income is the hardest part, and Agentic Document Extraction is the cornerstone to getting it right and traceable. Accurate data upfront means we can get a cleaner loan file to the underwriter and get to CTC faster. Get it wrong and everything downstream gets affected.”
View case study →Agentic Document Extraction has proven to be both accurate and easy to use. We are building on that foundation to deliver reliable, transparent, and scalable automation that our customers can validate and trust.”
View case study →Trust is the product. Accuracy alone isn’t enough at enterprise scale—what matters is provenance, traceability, and control. LandingAI gives us confidence that every extracted value can be traced back to its source, audited, and defended. That’s what makes it deployable in regulated, real-world environments.”
View case study →Our Plan Review Agent has a lot of complicated components under the hood: traversing building code knowledge graphs, reasoning across disciplines and sheets, assessing issues informed by historical projects. None of it works if we can’t trust what came off the page. ADE gave us a reliable foundation, so our team could focus on incorporating our team’s expertise into our compliance reasoning system.”
View case study →ADE has significantly outperformed other document extractors we’ve used. It has helped us build an Agentic RAG answer engine, based on unique healthcare institutional content, to offer instant, validated support to medical professionals at the point of care.”
View case study →I appreciate its reliability and the fact that they're constantly innovating with new models, which helps us work smarter. The service is essential for handling heavy workloads in financial institutions as it provides the necessary infrastructure for high accuracy and fast throughput. I also find it adaptable to specific use cases because they're always working on new models.”
We use LandingAI's Agentic Document Extraction to build pipelines that turn unstructured text into structured data. First, the NER (Named Entity Recognition) detection has amazing accuracy. Second, the OCR capability is excellent — earlier I had to run a separate PDF extractor for text plus a separate LLM with OCR to summarize images, and now it's one step. Third, the image boundary detection is a standout.”
We ran a structured bake-off: the same five PDFs (ranging from a 12-page slide deck to a 400-page machinery manual) processed through other products and Landing AI's Agentic Document Extraction (ADE). We scored each tool on four criteria: Table fidelity, Figure extraction, Chunk typing, Scale. Landing AI ADE was the only tool that scored well on all four.”
