1. Introduction and Goals
Requirements Overview
CREstimate.ai is an agentic AI system for commercial real estate valuations that addresses critical challenges in the traditional appraisal process:
The Problem:
- Subjectivity: Traditional appraisals rely heavily on individual appraiser judgment
- Inconsistency: Different appraisers produce different valuations for the same property
- Aging workforce: Average commercial appraiser age is over 60, creating supply constraints
- Outdated methodology: Excessive reliance on backward-looking data without systematic market sentiment analysis
The Solution: CREstimate.ai uses Smitty, an agentic AI economist that:
- Analyzes market sentiment through 6 data layers (macro-economic, micro-economic, geopolitical, capital markets, demographics, current events)
- Applies asset-specific weighting for different property types
- Continuously learns from historical outcomes via a memory bank
- Provides consistent, repeatable methodology
Core Capabilities
| Capability | Description |
|---|---|
| CRESI Calculation | Commercial Real Estate Sentiment Index with 6-layer analysis |
| Agentic Learning | Self-correcting AI that improves with each valuation |
| Asset-Specific Tuning | Different weighting for office, retail, industrial, multifamily |
| Audit Trail | Complete transparency into sentiment scoring methodology |
Quality Goals
| Priority | Quality Goal | Description |
|---|---|---|
| 1 | Architectural Clarity | Investors and partners understand technical approach without implementation details |
| 2 | Version Transparency | Track architectural evolution via changelog and semantic versioning |
| 3 | Accessibility | WCAG 2.1 AA compliance for all stakeholders including screen readers |
| 4 | Living Documentation | Fast updates during development with visible change indicators |
Stakeholders
| Role | Concern | Expected Outcome |
|---|---|---|
| Investors | Technical viability and ROI potential | Confidence in agentic AI approach and scalability |
| Strategic Partners | Integration capabilities and APIs | Clear boundaries, data flows, and partnership opportunities |
| Regulators | Compliance, auditability, risk | Documented quality requirements, risk mitigations, and methodology transparency |
| Technical Team | Implementation guidance | Arc42 blueprint for development decisions |
| Appraisers | Understanding AI role | How Smitty augments (not replaces) human expertise |
| Lenders/Banks | Valuation reliability | Consistent, defensible valuations for underwriting |
Business Context
Target Markets:
- Banks and lenders (licensing to banking software providers)
- Regulators (Fannie Mae, Freddie Mac, appraisal sub-committees)
- Private market investors (REITs, investment firms, brokers)
Business Model:
- Subscription-based with free tier
- One-time fees for full property reports
- Enterprise licensing for unlimited access
This documentation follows the arc42 template for software architecture documentation.