Automate Subcontractor Document Management with a Custom AI System

General contractors use Procore or Autodesk Construction Cloud for project management, but their document handling is generic storage. They can store a Certificate of Insurance (COI), but they cannot read the PDF to verify the policy limits match the contract requirements. This forces project managers to manually open and check hundreds of PDFs.

A GC with 7 active projects has 15 subcontractors on a new job. The project manager emails requests for COIs, W-9s, and safety plans. Two subs send an outdated COI, one sends a policy with liability limits below the $2 million required, and three forget to add the GC as an additional insured. The PM only discovers these errors by manually reading all 15 PDFs, a 4-hour task that delays onboarding.

Relying on email and generic cloud storage like Dropbox or SharePoint creates data silos. There is no central dashboard to see which subs on which projects are non-compliant. The workflow breaks because the tools treat documents as static files, not as sources of critical, structured data needed to manage project risk.

Syntora would approach the problem by first conducting a detailed discovery to understand your current document intake processes, critical document types, and compliance requirements. This initial phase involves identifying the key data fields to be extracted from documents like COIs and lien waivers (e.g., policy number, effective dates, coverage amounts).

The system would connect to your document source, whether it's an S3-compatible storage system via Python with the boto3 library, a shared drive, or a Procore account using the Procore API. Syntora would build a FastAPI service to orchestrate the entire document validation pipeline. When a new document is uploaded, a webhook would trigger an AWS Lambda function. This function would then send the document to the Claude 3 Sonnet API with a structured prompt designed to extract the necessary key fields into a JSON format. We have experience building similar document processing pipelines using Claude API for financial documents, and the same pattern applies effectively to construction-related documents. The extracted data would be securely stored in a dedicated Supabase table.

The core logic, implemented as Python functions, would compare the extracted data against your project-specific requirements, also stored in Supabase. This includes checking for valid policy expiration dates, ensuring coverage limits meet specified minimums (e.g., $2 million), and verifying 'additional insured' clauses. The validation results (pass, fail, or flagged for review) would be written back to a custom field in your project management tool via its API, providing immediate compliance status updates.

To provide visibility, Syntora would develop a simple, real-time dashboard using Vercel and Retool, offering an overview of subcontractor compliance across all active projects and proactively flagging expiring policies. For operational reliability, we would configure structlog for structured logging and set up CloudWatch alarms to send Slack notifications for any API error rate exceeding a defined threshold. Typical build timelines for a system of this complexity, including discovery and deployment, range from 8 to 16 weeks, depending on the number of document types and integration complexity. The client would typically need to provide access to existing document storage, project management APIs, and collaborate on defining compliance rules. Deliverables would include the deployed automation system, source code, documentation, and a knowledge transfer session.