IRRADIATION DC_POWER HEAT efficient
PRESSURE FLOW VELOCITY efficient
HEAT EXPANSION MOTION efficient
SILICON PV_CELL WAFER material
SEEDS PLANTS HARVEST farming
RAW_MATERIAL PRODUCT WASTE per se
BLUEPRINT SHAPE FORM formal
FERTILIZER GROWTH YIELD farming
FUEL COMBUSTION EXHAUST per se
VOLTAGE CURRENT POWER per se
FORCE ACCELERATION MOTION efficient
WATER GROWTH HARVEST farming
CATALYST REACTION PRODUCT efficient
MOLD CASTING PART formal
SPINDLE CUTTING CHIPS manufacturing
FEEDSTOCK OUTPUT HEAT material
OXYGEN COMBUSTION OXIDATION material
MACHINE OUTPUT WEAR final
TRAINING SKILL EXPERTISE efficient

Building AI that understands cause and effect

FinalAI develops causal AI systems that go beyond correlation to understand why things happen. We're building the foundation for intelligent systems that reason, not just predict.

Cause Effect Effect Effect

What We Do

Expert AI consulting and custom causal intelligence solutions

AI Assessment & Design

Using Kingdom, our proprietary causal AI engine, we assess your systems to understand the true causal structure of your domain. We design AI solutions grounded in rigorous ontological analysis, not just pattern matching.

Custom Causal AI Systems

Build bespoke AI systems that understand your domain's causal structure, enabling intervention planning, what-if scenario analysis, and genuine root cause identification.

ML Engineering

From object detection and classification to document analysis and tracking systems, we build production-ready ML solutions that integrate seamlessly with your infrastructure.

Root Cause Analysis

Go beyond descriptive analytics to understand why systems behave the way they do. Kingdom identifies per se causes, not just correlations, enabling true optimization.

Kingdom: Our Causal AI Engine

A novel approach to causal inference grounded in philosophical rigor and modern machine learning

# Kingdom discovers causal relationships
query("What causes output fluctuation?")

→ Analysis:
  • Efficient Cause: Control system instability
  • Material Cause: Environmental variations
  • Formal Cause: Design integrity intact
  • Final Cause: Goal misalignment

→ Confidence: 0.82
→ R² = 0.874 (87.4% explained)

What Makes Kingdom Different

  • Causal Discovery: Automatically discovers causal relationships from data, not just correlations
  • Cross-Domain Learning: Knowledge learned in one domain informs reasoning in others
  • Intervention Planning: Answer "what if" questions by understanding the causal structure
  • Philosophical Foundation: Built on rigorous Thomistic-Aristotelian principles of causation
  • Explainable: Every causal claim is traceable to its evidential source
345+
Causal Equations Discovered
87%
Average Variance Explained
Potential Domains

Trusted by Industry Leaders

Our team has contributed to cutting-edge projects across multiple industries

Meet the Team

Experts at the intersection of AI, philosophy, and engineering

PC

Patrick Creamer

Co-Founder & Chief Systems Architect

Systems Engineering & Philosophy. Patrick brings deep expertise in process causation and systems thinking to design AI that understands not just patterns, but the fundamental why behind complex phenomena.

Systems Engineering Process Causation Domain Modeling Causal AI
LV

Luis Valle

Co-Founder, Chief AI Architect

ML & Software Engineering, Philosophy. Creator of Kingdom. Expertise in classification, regression, tracking, planning, and control systems. Bridges philosophical rigor with cutting-edge machine learning.

Classification Regression Planning & Control Causal AI

Let's Work Together

Whether you need AI strategy consulting, custom ML solutions, or want to explore causal AI for your domain, we'd love to hear from you.