The CRE Professional's Guide to Evaluating AI Tools
AI tools are flooding the commercial real estate market. Every vendor claims to “transform your workflow” and “save hours.” But CRE has unique requirements that most AI tools aren't built to handle. Here's a practical framework for evaluating AI tools for your organization.
Question 1: Where Does My Data Go?
This is the most important question, and it should be your first.
- Ask: When I upload or query a document, where is it processed?
- Ask: Is my data used to train or improve the AI model?
- Ask: Can I keep AI processing within my infrastructure?
- Red flag: Vague answers about “enterprise-grade security” without specifics on data flow.
CRE documents contain confidential rent figures, deal terms, and financial performance data. Your IT security and legal teams will want concrete answers about data handling.
Question 2: How Accurate Are the Answers?
Accuracy has two dimensions in CRE AI:
Grounding: Does It Read My Documents?
General AI tools answer from training data — they don't know what's in your leases. Look for tools that actually retrieve and read your specific documents (this is called RAG — Retrieval-Augmented Generation). If the tool can't cite the specific document it drew an answer from, proceed with extreme caution.
Verification: Can I Check the Source?
Source citations aren't a nice-to-have — they're essential. When the AI says the base rent is $32.50/SF, you need to click through to the lease section that says exactly that. Without citations, you're trusting the AI blindly.
Question 3: Does It Work With My Existing Tools?
CRE organizations have established document management workflows. Evaluate:
- Document storage integration: Can it connect to your existing repository (Egnyte, SharePoint, etc.) or do you need to upload files manually?
- Authentication: Does it support SSO through your identity provider (Microsoft Entra ID, Okta)?
- No migration required: The best tools read from where your documents already are. If a tool requires migrating your entire document library, factor in that cost and risk.
Question 4: Is It Built for CRE?
Generic AI can have a conversation. CRE-specific AI understands your domain:
| Capability | Generic AI | CRE-Specific AI |
|---|---|---|
| Understands lease terminology | Basic | Deep (CAM, NNN, co-tenancy, etc.) |
| Reads rent rolls & financials | Generic table reading | CRE-specific column recognition |
| Cross-property queries | N/A | Built-in portfolio intelligence |
| Folder structure awareness | None | Understands property/doc-type hierarchy |
Question 5: What Does the Total Cost Look Like?
Beyond the subscription price, consider:
- Per-query costs: Some tools charge per API call or per document processed
- Migration costs: Time and effort to move documents or integrate systems
- Training costs: How long does it take your team to become productive?
- Ongoing maintenance: Does it require dedicated IT resources?
Question 6: What About Team & Compliance Features?
Enterprise CRE organizations need:
- Role-based access control (who can see what)
- Audit logging (who accessed which documents and when)
- Multi-tenant data isolation (if managing multiple client portfolios)
- Conversation sharing (for team collaboration on research)
The Evaluation Checklist
- ☐ Data stays within my infrastructure (or clear data handling policy)
- ☐ Answers cite specific source documents
- ☐ Connects to my existing document storage
- ☐ SSO authentication supported
- ☐ Understands CRE-specific terminology and documents
- ☐ Role-based access control
- ☐ Audit trail for compliance
- ☐ Multi-document search (not just single-file upload)
- ☐ No data used for AI model training
- ☐ Transparent pricing without hidden per-query costs
See How Sevrel Measures Up
Sevrel checks every box on this list. See it in action with your documents.
Last updated: March 15, 2026