Problem 01 — Escape Routing (NP-Hard)
One aircraft. Three SAM sites locked on. A drone swarm closing the gap. Fuel below reserve, flares nearly spent. Seven seconds. Billions of possibilities. One decision — what do you do?
Global-scale problems demand global-scale knowledge.
And global-scale knowledge requires leading-scale partnerships.
This is a technology race that, together, we cannot afford to lose. The rewards of winning benefit everyone. When you cannot afford to be wrong, the answer cannot be approximated — and it does not belong in a black box.
D33 AI · Quantum in full alignment with the United States Genesis Project — open to strategic partnerships sharing the same goals.
Example problems where classical and quantum computing — and the thousands of tests in between — get you the world's toughest solutions.
Classical · Quantum · Thousands of Tests for Everything in Between
Problem 02 — Portfolio Rebalance (Combinatorial)
Five hundred assets. Thousands of constraints — exposure, liquidity, tax lots, correlation drift. What is the optimal rebalance, not the approximation everyone settles for?
Problem 03 — Global Logistics (NP-Hard)
Thousands of empty containers. Five upcoming ports, uneven demand, finite vessels, repositioning costs that compound. What plan minimizes empty containers across the entire network at once?
Problem 04 — Multi-Vehicle Estate Optimization
A $200M family balance sheet across three generations. Estate, charitable vehicles, and tax-lot selection — eight coupled decision categories, ~10²²⁰ configurations. What single joint-optimal plan beats the competent sequential one Markowitz can't even formulate?
Trust isn't something we ask you to rely on.
We provide mathematical proofs and full audit trails through our rigorous 10-step process. Every answer can be checked, re-derived, and defended.
If you don't trust math, we're probably not a good fit for you.
This shifts the HNW planning playbook.
D33.AI finds a second quantum-enhanced solution to Markowitz's limits — multi-vehicle joint optimization, solving the combinatorial problems mean-variance theory cannot formulate.
Case Study: Multi-Vehicle Joint Optimization
Representative $200M family · three generations · California · 2026 decision year
"Find the optimal 2026 estate, charitable, and tax-lot strategy across the entire family balance sheet — jointly, not sequentially."
- 10²²⁰ Decision Search Space — configurations across the granular tax-lot layer
- $72.6M Total Economic Lift — vs. a competent sequential plan, 20-yr horizon
- $44.1M Estate Tax Saved — refined and proof-backed, net of forfeited step-up
- 3 Generations Impacted — optimized jointly across G1, G2, G3
Beyond Quantum: AI, ML, Automation, and Physics Simulation
Quantum optimization is one layer of the D33 platform. The full stack spans custom AI and machine learning models, intelligent automation, and physics-based simulation — all built to the same standard of verifiability.
The team behind D33 AI Labs
Kellar — Founder, CEO / CTO
Quantum computing, machine learning, and infrastructure architecture. Advanced Quantum Computing certification.
Kellar@d33ai.comTroy — Chief Operating Officer
Operations and strategic execution.
Kevin — Lead Strategic Advisor, Government Affairs & Defense
United States Naval Aviator and Officer. Grounds D33's defense and national-security work in real operational reality — translating mission requirements, doctrine, and the constraints of the field into the problems our platform is built to solve.