Investment Scoring
“Which properties offer the best risk-adjusted return?”
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A real-world example
Which properties offer the best risk-adjusted return?
Real estate funds evaluate 100+ properties per acquisition, spending $50K-$200K in due diligence per deal. Traditional underwriting models project returns using historical cap rates and comparable sales, missing the demographic and economic graph signals that drive future performance. For a fund deploying $500M annually, improving deal selection by identifying the top-quartile properties saves $20-40M in avoided underperformance over a 5-year hold period.
How KumoRFM solves this
Graph-powered intelligence for real estate
Kumo connects properties, financials, market data, demographics, and transactions into an investment graph. The GNN learns which property-market-demographic combinations produce outsized returns: how population growth corridors interact with supply pipelines, how employment center proximity affects rent growth, and how comparable transaction patterns signal market turning points. PQL scores each property by predicted risk-adjusted return, enabling funds to focus due diligence on the highest-potential deals.
From data to predictions
See the full pipeline in action
Connect your tables, write a PQL query, and get predictions with built-in explainability — all in minutes, not months.
Your data
The relational tables Kumo learns from
PROPERTIES
| property_id | type | units | year_built | market |
|---|---|---|---|---|
| INV001 | Multifamily | 120 | 2010 | Austin |
| INV002 | Office | 50K sqft | 2005 | Denver |
| INV003 | Multifamily | 200 | 2018 | Nashville |
FINANCIALS
| property_id | noi | cap_rate | occupancy | rent_growth_yoy |
|---|---|---|---|---|
| INV001 | $2.4M | 5.2% | 95% | +4.8% |
| INV002 | $1.8M | 6.8% | 82% | -2.1% |
| INV003 | $3.6M | 4.8% | 97% | +6.2% |
MARKET_DATA
| market | population_growth | job_growth | supply_pipeline | rent_trend |
|---|---|---|---|---|
| Austin | +3.2% | +4.1% | High | Rising |
| Denver | +1.5% | +1.8% | Medium | Flat |
| Nashville | +2.8% | +3.5% | Medium | Rising |
DEMOGRAPHICS
| market | median_age | median_income | renter_pct | tech_employment_pct |
|---|---|---|---|---|
| Austin | 34 | $72,000 | 48% | 18% |
| Denver | 36 | $68,000 | 42% | 12% |
| Nashville | 35 | $58,000 | 45% | 8% |
TRANSACTIONS
| txn_id | market | type | price_per_unit | cap_rate | date |
|---|---|---|---|---|---|
| TXN301 | Austin | Multifamily | $210K | 5.0% | 2025-01-15 |
| TXN302 | Denver | Office | $320/sqft | 7.2% | 2025-02-01 |
| TXN303 | Nashville | Multifamily | $185K | 4.9% | 2025-02-20 |
Write your PQL query
Describe what to predict in 2–3 lines — Kumo handles the rest
PREDICT AVG(FINANCIALS.noi, 0, 365, days) / PROPERTIES.asking_price FOR EACH PROPERTIES.property_id RANK TOP 10
Prediction output
Every entity gets a score, updated continuously
| PROPERTY_ID | MARKET | 5YR_IRR | RISK_SCORE | RANK |
|---|---|---|---|---|
| INV003 | Nashville | 14.8% | Low | 1 |
| INV001 | Austin | 12.2% | Medium | 2 |
| INV002 | Denver | 7.4% | High | 3 |
Understand why
Every prediction includes feature attributions — no black boxes
Property INV003 -- 200-unit Multifamily in Nashville
Predicted: 14.8% projected 5-year IRR (Rank #1, Low risk)
Top contributing features
Rent growth trajectory
+6.2% YoY, accelerating
29% attribution
Occupancy stability
97% (above market)
24% attribution
Population + job growth momentum
+2.8% / +3.5%
20% attribution
Moderate supply pipeline (no oversupply)
Medium
16% attribution
Comparable transactions support valuation
$185K/unit
11% attribution
Feature attributions are computed automatically for every prediction. No separate tooling required. Learn more about Kumo explainability
PQL Documentation
Learn the Predictive Query Language — SQL-like syntax for defining any prediction task in 2–3 lines.
Python SDK
Integrate Kumo predictions into your pipelines. Train, evaluate, and deploy models programmatically.
Explainability Docs
Understand feature attributions, model evaluation metrics, and how to build trust with stakeholders.
Bottom line: A fund deploying $500M annually saves $20-40M over a 5-year hold by improving deal selection. Kumo's investment graph connects property financials to demographic momentum and supply dynamics, scoring deals by predicted risk-adjusted return rather than historical cap rates alone.
Related use cases
Explore more real estate use cases
Topics covered
One Platform. One Model. Predict Instantly.
KumoRFM
Relational Foundation Model
Turn structured relational data into predictions in seconds. KumoRFM delivers zero-shot predictions that rival months of traditional data science. No training, feature engineering, or infrastructure required. Just connect your data and start predicting.
For critical use cases, fine-tune KumoRFM on your data using the Kumo platform and Data Science Agent for 30%+ higher accuracy than traditional models.
Book a demo and get a free trial of the full platform: data science agent, fine-tune capabilities, and forward-deployed engineer support.
