Predictive analytics · Governed machine learning · Active build

We built the full stack for predictive investment intelligence.

SparkData Analytics engineered the complete chain — point-in-time market data, a ten-factor market-intelligence engine, transparent model training, economic stress-testing, byte-identical reproduction — and made it run as one system. Infrastructure first. Signals when they're earned.

6,156 point-in-time market rows10 factor intelligence engine13 promotion gates3 identical reproductions
The system in motion

The whole stack, in 59 seconds.

Watch SDA turn frozen market evidence into trained models, gated decisions, and validation anyone can re-run. Hover for an instant muted preview. Open the film and turn sound on for the score.

Investment Intelligence full-stack campaign artwork Hover: instant preview · Click: full film + score · 0:59
Five connected disciplines

The SDA method, made operational.

Five disciplines, wired into one pipeline. Each one exists because a real failure mode exists without it.

01

Control the evidence

6,156 point-in-time rows spanning 2020–2026, frozen before any model sees them. No hindsight. No leakage.

02

Model the mechanisms

A ten-factor macro and market-regime engine reads the environment every candidate model will operate in.

03

Train transparently

A six-feature Ridge candidate — every coefficient inspectable, nothing black-box.

04

Test economically

Thirteen promotion gates: walk-forward, holdout, cost, stress, multiple-testing, and live-forward controls.

05

Reproduce independently

Three executions, byte-identical. If it can't be reproduced, it doesn't count.

Inspectable by design

A system that can show its work.

The public film is concise. The system beneath it freezes inputs, trains and validates candidate models, tests economic feasibility, and preserves the evidence behind each outcome.

6,156point-in-time rows, frozen before modeling — a dataset that can't cheat
14input datasets, zero missing values — complete evidence, no patched holes
9audit-ready artifacts from every run — decisions you can defend later
3independent executions, byte-identical — results that survive re-running
The SDA signature
Every signal has to be earned.

Thirteen promotion gates stand between a trained model and a live decision. The system will emit nothing before it emits something unearned. It's the same standard that carried our AI tax agent through live software review: evidence in, gates enforced, no unearned yes.

See that standard at work →
The model inside the machine

Transparent by construction.

The current candidate is deliberately inspectable: six frozen features, one Ridge family, three preregistered penalty strengths. The model is one continuously improving component inside the larger intelligence system.

MODELRidge regression
FEATURES6
FITTED ROWS180
ALPHAS3
STATUSIn development · not yet promoted
Current development milestone

The complete chain runs today.

The latest research cycle ran the entire chain end to end — data freeze, training, thirteen-gate evaluation, three byte-identical reproductions, 523 tests at 91.58% coverage — and hardened the evidence and validation controls along the way. No candidate model has been promoted to live use yet; promotion is earned through the gates, and the gates are enforced. Signal research and model advancement are active.

Every cycle makes the system harder to fool.
What the platform connects

Micro, meso, and macro intelligence in one governed pipeline.

Financial conditions & ratesReal policy rates, TIPS, mortgages, stress indexes, and the yield curve.
Inflation & expectationsCPI, PCE, survey expectations, and breakeven inflation.
Credit & lendingInvestment-grade and high-yield spreads plus bank lending standards.
Liquidity & volatilityReserves, Treasury cash, dollar conditions, money growth, and VIX state.
Energy & real economyOil, gasoline, natural gas, credit impulse, and market transmission.
Equity intelligenceSector rotation, issuer evidence, factor features, model scores, and constrained portfolio tests.
Evidence before adjectives

Built to learn. Engineered to prove it.

Most predictive-analytics marketing shows you a backtest and asks for trust. We built the opposite: a system whose every claim is frozen, gated, and reproducible before it's allowed to matter. When this system puts a signal forward, you'll be able to check its work — because checking its work is the product.

01Evidence frozenKnown-time inputs preserved before training.
02Gates enforcedEconomic and operational controls decide promotion.
03Results reproducibleIndependent executions resolve to identical artifacts.
The proof is public

See it run. Then put it to work.

Watch the film — no login required. If your firm needs AI it can defend, not just demo, this is what that looks like in practice.