One codebase. Eight domains. 2,050+ discovered equations. Real results from a single execution — no iterative tuning, no domain-specific engineering.
Every industry has the same problem: too much data, not enough understanding of what's actually driving outcomes. Existing tools predict, but none of them can hand you the governing equation so you can verify it yourself. We built one system that discovers interpretable mathematical equations across any domain — and validates them rigorously before they reach a client.
Built the core engine and led validation across all eight domains. Responsible for the technical vision, product architecture, and every published result. The same system that projected Aaron Judge's home runs discovered hospital readmission equations and cap rate structures in CRE.
Leads business operations, financial strategy, and go-to-market execution. Identifies high-value verticals, structures commercial partnerships, and builds the operational foundation to scale from proof-of-concept to revenue. Ensures the business side moves as fast as the technology.
Building an equation for one dataset is straightforward. Building infrastructure that discovers validated equations across eight unrelated industries with a single codebase requires solving problems most teams never encounter.
Baseball, healthcare, residential and commercial real estate, retail, transportation, oil & gas, and water systems. Every result was produced by the same unmodified engine. A competitor entering one vertical starts from scratch.
Every new domain strengthens universal law discovery. Every universal law strengthens every client's Elijah. The more domains connected, the wider the moat. Early participants benefit most from every domain that connects after them.
Unlike ML models that require retraining, validated mathematical equations are permanent additions to the knowledge base. They don't lose accuracy as the world changes. The equation library only grows.
Black-box models cannot explain why. Elijah produces readable equations, sensitivity analysis, feedback loops, and forward projections that domain experts can inspect, challenge, and trust.
The system finds relationships nobody was looking for. Cross-category revenue dependencies in retail. Biomarker interaction equations in healthcare. Migration pull factors in real estate. The discovery capability is what makes it commercially valuable.
michael.lazzarotti@diginetics.co