The honest comparison
For long, rule-bound commercial real estate documents, PSV builds on Claude by Anthropic, which is well-suited to long context and detailed, multi-step instructions across a single session, from the first page of an offering memorandum to the last. ChatGPT is capable and widely used. For CRE the deciding factor is less the brand and more how the model is set up: grounded in your actual files, constrained to your rules, and asked to show the source behind each number.
Where each model fits
Reading a 60-page OM or a messy rent roll rewards steady long-context instruction following, which is why PSV standardizes on Claude for the deal documents.
Quick research, brainstorming, and short drafting are well served by either model. The choice matters far less here than on long, rule-bound documents.
The mistake operators make is expecting either model, unassisted, to underwrite accurately from a raw file. Both work best with a grounded setup and source citation before their numbers go to committee.
How to set either model up for CRE
Upload the real OM, rent roll, and T-12. A model working from your documents beats one answering from general knowledge.
Tell it your underwriting assumptions, thresholds, and the exact template to fill, so the output arrives in a form you can use.
Require the rent, page, or line behind each figure, so a person can verify every number before it reaches committee.
This grounded, cited setup is exactly what the CRE AI Institute teaches, and what PSV builds for firms that want it deployed across the team.
Frequently asked
The CRE AI Institute teaches how to set up Claude to read OMs, rent rolls, and T-12s and show its work, on a real practice deal. 7-day free trial.