- What is an AI agent for commercial real estate?
- An AI agent for commercial real estate is a model like Claude given standing instructions, access to your deal files, and defined tools, so it can carry a full workflow such as screening a deal or abstracting a T-12. Unlike a chat, it follows your rules every time and returns output in a format your team reviews.
- How is an AI agent different from a chatbot?
- A chatbot answers the question in front of it and forgets the context when the conversation ends. An agent owns a step of your pipeline: it starts from your rules, works from the real files, and produces the same reviewable output every run.
- How do I build an AI agent for real estate?
- Pick one defined workflow, write down the rules you already apply, give Claude those instructions plus the relevant deal files, and require a source citation behind every number. Keep a person signing off on the output. The CRE AI Institute teaches this build step by step on a real practice deal.
- Do I need to code to build an AI agent?
- No. The instructions that define an agent are written in plain English: what to check, which assumptions to apply, what the output must look like. Code becomes relevant when a firm wants agents wired into its systems, which is the kind of build PSV does for enterprise clients.
- Should I buy an AI agent product or build my own?
- Buying is really renting: your files flow through someone else's system and the reasoning stays hidden. Building means the agent runs on your files, in your environment, with a citation trail you keep. Start by learning how one works; the build is smaller than most operators expect.
- What can an AI agent do for a CRE team?
- Well-defined document workflows suit agents best: screening incoming deals against your criteria, abstracting a T-12 or rent roll into your template, and drafting an IC summary with sources attached. A person reviews every output before it moves forward.