Quant for CRE.
Math you can defend in IC.
Once your data is clean, we layer the models institutional quant funds run on capital markets, adapted for CRE. Regression. Forecasting. Monte Carlo. Predictive scoring. Every output cites lineage. The AI never invents a number.
Pipeline Score · Active Deals
Pursue
3
Watch
1
Pass
1
94
score
Magnolia Lofts
Austin TX · 215 units
87
score
Cypress Creek
Houston TX · 350 units
81
score
Riverside Tower
Tampa FL · 320 units
64
score
Park Place
Phoenix AZ · 180 units
42
score
Brookhaven
Atlanta GA · 192 units
Inputs: deal fit · seller propensity · submarket supply · time-to-close
Regression-scored
Pipeline Intelligence
Score every deal. Rank the pipeline.
Deal scoring against your investment view. Seller-propensity models surface owners likely to sell. Time-to-close forecasts prioritize what will actually transact.
- Deal fit score: vintage, micro-location, supply, capital stack
- Seller-propensity scoring on historical ownership turnover
- Broker performance: hit rates, mark-to-market accuracy
- Time-to-close forecasts so the team focuses on what closes
Submarket Score · Sunbelt MF
Strong
3
Good
3
Austin
78704
92
Houston
77024
85
Tampa
33602
78
Dallas
75201
74
Orlando
32801
68
Charlotte
28202
64
Phoenix
85016
56
Nashville
37203
51
Atlanta
30309
44
Refreshed daily
Market Intelligence
Zip-level signal. Submarket scoring.
Supply pipeline, demographics, rent growth, and rates fused into a single submarket score. Automated daily across every market you target.
- Zip-level supply pipeline plus demographic and migration data
- Submarket scoring surfaces emerging micro-markets early
- NIMBY and entitlement indicators (where supply will actually get built)
- Rent-comp regression: how much of variance is signal vs. noise
Variance Attribution · Fund III
YTD NOI vs UW
Net Variance
+$0.42M
vs underwriting
By driver
Rent growth above UW
+$1,240K
Occupancy gain
+$580K
Other income lift
+$210K
Turnover overrun
−$420K
Insurance reset
−$880K
Tax reassessment
−$310K
Lineage: Yardi GL · RealPage rent rolls · CoStar comps. Every number cited.
Portfolio Intelligence
Hold periods. Dispositions. Variance.
Hold-period optimization tells you when to sell. Monte Carlo stresses every hypothesis. Variance attribution explains why actuals diverged from underwriting, traced to source.
- Hold-period optimization: supply, rent forecasts, cap-rate paths, refi optionality
- Disposition timing tied to LP waterfall mechanics and fund cycle
- Variance attribution: actuals vs UW by driver, cited to source
- Monte Carlo with P10 / P50 / P90 bands on every deal
Hold-Period Optimizer · Cypress Creek
Optimal exit
Year 5
22.4%
levered IRR
Levered IRR by exit year
14.2%
Y3
18.6%
Y4
22.4%
Y5
Optimal
21.1%
Y6
18.8%
Y7
UW Exit
Year 7
UW IRR
19.0%
Upside
+340 bps
Operator built
Underwriters who learned to code.
Every signal maps back to a line item your IC already reviews. Pro formas, waterfalls, lease economics. No black boxes. No model in search of a deal.
You set the thesis. The models apply it.
Built by underwriters who learned to code. The math ties. The audit trail is yours.