Intelligent Valuation Workflow Digital Worker
Implements a 6-agent ReAct pattern workflow that analyzes 800K+ historical valuations using collaborative filtering to recommend optimal products, matches appraisers using multi-criteria decision analysis (MCDA), and predicts QC outcomes before order placement. Reduces costs while maintaining acceptance rates.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
AI Agents
Specialized autonomous agents working in coordination
Orchestrator Agent
Valuation workflows involve multiple specialized analyses that must be coordinated efficiently with proper data flow between agents.
Core Logic
Coordinates the 7-phase workflow from data collection through final synthesis. Delegates tasks to specialized agents, aggregates results, and generates unified recommendations. Manages comparable sales searches and property data lookups through tool calling.
Risk Analysis Agent
Property and loan risk factors must be assessed to determine appropriate valuation rigor and identify potential issues before ordering.
Core Logic
Runs logistic regression model analyzing 10 risk factors including LTV ratio, property age, market volatility, and comparable availability. Calculates probability of default with confidence intervals, assigns risk tiers (very-low to high), and identifies top contributing factors for transparency.
Product Recommendation Agent
Selecting between Desktop, Hybrid, and Full Appraisals requires balancing cost, turnaround, and acceptance risk based on property characteristics.
Core Logic
Applies item-item collaborative filtering on 800K+ historical valuations to identify similar properties and their outcomes. Uses Bayesian confidence scoring to calculate acceptance likelihood for each product type, then optimizes for cost-benefit tradeoffs.
Appraiser Matching Agent
Optimal appraiser selection requires balancing expertise, performance history, turnaround speed, and current workload across large panels.
Core Logic
Implements Multi-Criteria Decision Analysis (MCDA) with Weighted Sum Model scoring 5 criteria: Historical Performance (30%), Property Expertise (25%), Turnaround Speed (20%), Quality Trend (15%), and Current Capacity (10%). Evaluates 20+ appraisers to find optimal match with alternatives ranked.
Quality Control Agent
QC revisions delay closings and increase costs. Predicting likely issues before order placement enables preventive guidance.
Core Logic
Analyzes historical QC patterns for similar property types and locations to predict likely issues (comparable selection, adjustment consistency). Generates preventive recommendations for appraisers such as verifying comp sales in MLS and documenting unusual characteristics. Pass likelihood prediction accuracy: 96%.
Compliance Agent
Valuation recommendations must comply with USPAP standards, Fannie Mae guidelines, state requirements, and investor overlays.
Core Logic
Validates proposed recommendations against USPAP 2024 Standards, Fannie Mae Selling Guide requirements, state-specific regulations, and investor overlay rules. Verifies appraiser independence requirements. Generates compliance status with detailed check results for audit purposes.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
4 technologies
Architecture Diagram
System flow visualization