AI with Project Data
AI systems that work directly with construction project data, documents, and drawings.
Definition
AI with Project Data refers to artificial intelligence applications that ingest, process, and analyze the complete spectrum of construction project information—including drawings, specifications, schedules, RFIs, submittals, meeting minutes, and correspondence. These systems transform unstructured project data into AI-ready formats, enabling intelligent search, automated analysis, and AI-powered workflows. By understanding project context and relationships between different document types, these AI systems provide more accurate and useful insights than generic AI tools.
In Depth
AI with project data — connecting AI to the actual specifications, drawings, submittals, RFIs, and correspondence for a specific project — is the fundamental use case that makes AI practical for construction. Without access to project data, AI can only provide generic answers. With access, it becomes a project-specific knowledge assistant.
The connection happens through integration with the project's document management platform — Procore, SharePoint, Egnyte, ACC, or other systems. AI indexes the project documents, understands their structure and relationships, and makes the entire project knowledge base queryable through natural language. The result is that any team member can get cited answers from the project documents in seconds.
Examples
Making all project documentation searchable and queryable with AI
Automatically linking related information across drawings, specs, and RFIs
Extracting insights from project data to improve future projects
Nomic Use Cases
See how Nomic applies this in production AEC workflows:
Compatible Platforms
Nomic integrates with these platforms so you can use ai with project data across your existing project data:
Frequently Asked Questions
AI with Project Data refers to artificial intelligence applications that ingest, process, and analyze the complete spectrum of construction project information—including drawings, specifications, schedules, RFIs, submittals, meeting minutes, and correspondence. These systems transform unstructured project data into AI-ready formats, enabling intelligent search, automated analysis, and AI-powered workflows. By understanding project context and relationships between different document types, these AI systems provide more accurate and useful insights than generic AI tools.
Making all project documentation searchable and queryable with AI. Automatically linking related information across drawings, specs, and RFIs. Extracting insights from project data to improve future projects.
Project Research: Instantly access all project-critical information from a single search interface.