How It Works — Predictive Funding Intelligence
The Pipeline

From raw scenario to
scored outcome — in four moves.

No documents. No credit pull. You describe the deal, the engine runs four passes, and you get a scored sheet back that names every signal it weighed, the reading on each scale, and the ranked changes that lift the file's funding probability.

Run a Deal Through the Pipeline Inside the Engine
01 // INGEST
Raw scenario in
asset · sponsor · structure
02 // SCORE
140+ signals weighted
sponsor · asset · market
03 // FORECAST
Four outcomes modeled
FPI · SSR · SRS · RP
04 // RECOMMEND
Ranked fixes out
cost · impact · effort
92%
Prediction Accuracy
< 4m
Median Runtime
0
Credit Pulls
12
Output Fields
STEP 01

Ingest the deal.

Most files arrive as a phone call, a sloppy memo, or a screenshot of an LOI. The ingest pass strips the narrative and resolves it into the structured signals the model requires — without ever pulling credit or asking for tax returns.

// Data In
# raw description "$12.5M multi, 80 units, Tampa, value-add reno, sponsor has 3 prior."
// Data Out
# structured signals asset.class multifamily asset.units 80 asset.market Tampa FL sponsor.prior 3 verified debt.req $12,500,000
STEP 02

Score the signals.

The model weighs 140+ data points the way capital sources actually evaluate risk and return. Each signal gets a weight, each weight gets a confidence score, and the model knows the difference between ‘strong sponsor’ and ‘strong sponsor on this asset class in this market this quarter.’

// Signals In
  • Sponsor signals (32) — experience, liquidity, credit
  • Asset signals (38) — class, geography, condition
  • Market signals (29) — supply, rent growth, cap rates
  • Structure signals (24) — LTV, DSCR, reserves
  • Context signals (19) — rates, agency depth, urgency
// Scored Out
# per-signal weights applied sponsor.weight 0.31 asset.weight 0.27 market.weight 0.18 structure.weight 0.16 context.weight 0.08 # sum → composite signal
STEP 03

Forecast the outcomes.

The composite signal resolves into four independent forecasts — Funding Probability, Sponsor Strength, Stabilization Risk, Refinance Probability — each generated by its own scoring head so a weak signal in one dimension doesn't quietly drag down the others.

// Composite In
# weighted signals signal.composite computed confidence 0.91 data.completeness 94%
// Forecasts Out
funding_probability 82 / 100 sponsor_strength A− stabilization_risk 28 / low refinance_probability 75% # four heads, one verdict
STEP 04

Recommend the fixes.

The final pass reads the forecasts and asks: what changes would move them the most? You get a ranked list of specific adjustments — each one tagged with its projected score impact, the cost or effort to execute, and which forecast it moves.

// Forecasts In
fpi 82 # could be 89 ssr A− # strong, hold srs 28 # low, hold rp 75 # could be 82
// Ranked Fixes Out
fix.01 LTV 75 → 68% impact +7 FPI fix.02 12mo IO reserve impact +4 FPI, +5 RP projected FPI 89 · RP 82
What You Receive

Every run produces a single, defensible score sheet.

The Score Sheet

One page. Four forecasts. Every signal that fed them, named. Built to be read by a senior reviewer in 90 seconds.

The Signal Trace

Behind every score is the full list of inputs and their per-signal weights. No black box. Defend any reading to a borrower or a lender.

The Fix Set

Ranked, specific moves that lift the forecast. Each tagged with cost, effort, and projected score impact — not generic advice.

Predict Your Next Close

Get your funding score in minutes — no credit pull, no commitment.

See where your deal stands and exactly what to fix before you ever submit it to capital.

Get Your Funding Score Talk to an Expert