You can paste document text or upload files into ChatGPT, but there are significant limitations for AEC work. ChatGPT has no persistent project memory — every session starts fresh. It cannot parse construction drawing files to understand what is shown on specific sheets. And it will hallucinate answers when it does not know something, which creates real risk for code compliance and specification questions. Nomic is specifically designed to prevent these issues for AEC document workflows.

Nomic uses a combination of foundation models including models from OpenAI, but the key difference is the domain-specific layer: custom models trained on hundreds of thousands of AEC drawings, a 380-code compliance database with curated citations, and a retrieval architecture that ensures every answer is grounded in your actual project documents. The raw OpenAI API without this AEC-specific layer will produce unreliable results for construction document workflows.

ChatGPT's free and Plus tiers use conversation data for model training by default, which creates confidentiality risks for project documents. The Enterprise plan provides data isolation and a commitment not to use your data for training. Nomic is SOC 2 Type II certified, offers a zero data retention option, and supports multi-region data hosting (EU, AU, US, UK) for firms with data residency requirements.

Nomic can parse construction drawing files and answer questions about what is shown on specific sheets — something ChatGPT cannot do even with image upload, because it does not understand AEC drawing conventions. Nomic checks your specific drawings against 380 current building codes and returns cited compliance reports. It integrates directly with Autodesk Construction Cloud, Bentley ProjectWise, SharePoint, Egnyte, Fieldwire, Google Drive, Box, and Dropbox to pull documents without manual uploads. And every answer it gives is grounded in a source document — it will not invent answers.

Many AEC firms do. Nomic handles project-document work where accuracy and grounding matter: drawing review, code compliance, submittal review, and specification search. ChatGPT handles broader writing tasks: proposals, client communications, general research, and tasks that do not require project-specific knowledge. The tools are largely complementary rather than competing for the same use cases.

Not for the document-heavy tasks at the center of AEC work. Through 2026, general-purpose frontier models continue to underperform purpose-built AEC tools on specialized construction drawing tasks, because they are not trained on drawing conventions and have no grounding in your project files. Purpose-built vertical tools like Nomic, which are trained on construction drawings and connected to your project documents, materially outperform general models on drawing review, code checks, and submittal review. ChatGPT remains excellent for the general writing and research that sits around those workflows.