Why Accuracy Matters More Than Speed in CRE Document Analysis
In a world obsessed with AI speed benchmarks, CRE professionals know the truth: a wrong number delivered instantly is worse than the right number delivered in 30 seconds. Here's why accuracy should be your primary criterion when evaluating AI for document analysis.
The Cost of Wrong Numbers
When an AI tells you the base rent is $28/SF when it's actually $32.50/SF, the consequences cascade: your underwriting model uses the wrong figure, your investor memo contains incorrect data, and your negotiation strategy is built on a false premise. In CRE, a single inaccurate data point can cost thousands.
What Makes AI Answers Accurate
- Document grounding (RAG): Answers come from your actual files, not training data
- Source citations: Every claim links to the specific document section
- Grounding guards: Automated checks that responses match retrieved documents
- CRE-aware prompting: The AI knows that financial figures must come from documents, never from general knowledge
Speed vs Accuracy: The Right Balance
This isn't about being slow. Sevrel answers most queries in under a minute — far faster than manual document review. The point is that the architecture prioritizes getting the right answer over getting any answer fast. When the AI isn't confident, it says so rather than generating a plausible guess.
Fast
Fastest responses. Great for routine lookups where the answer is straightforward.
Standard
Balanced speed and reasoning depth. The default for RAG queries and general analysis.
Deep
Deepest reasoning. Best for complex analysis where accuracy requires more careful interpretation.
Sevrel routes every query to the right tier automatically — no manual switching.
The Verification Workflow
The best AI workflow for CRE: AI extracts and compares, humans verify and decide. Source citations make verification a 10-second click instead of a 10-minute search. This is the right balance of speed and accuracy.