DeFi All Odds (Patent Pending Technology) brings validated supply intelligence, mission readiness insight, personnel, and statistical simulations together for Army organizations operating in complex environments.
Certainty for every mission variable.
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AI & Supply Chain Validation
Create a digital twin and ledger to verify physical tracking devices.
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Mission Readiness
Turn logistics, personnel, and operational signals into a clearer view of preparedness at every decision point.
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Statistical Simulations
Model uncertainty, compare courses of action, and make decisions with high confidence.
Submitted Contracts
Image | Description | Date Applied | Title | Amount |
|---|---|---|---|---|
READINESS SIMULATION | 8/14/2026 | Selective Service System | $6,700,000 | |
In Transit Visibility in Blockchain | 6/1/2026 | ARMY | $300,000 | |
Digital Twin of The Organization for Enhanced Mission Readiness | 7/17/2026 | Defense Logistics Agency | $100,000 |

Past Performance
Customer/Organization Name: National Science Foundation
Short description and projects:
NSF SBIR Phase I: "Interest-Based Learning Management System to Ensure University Students are Qualified to Gain Web3 Careers," awarded in 2024. Development and feasibility testing of an interest-based learning and career-matching system for university students pursuing emerging-technology careers, completed in 2024.
Contract Number: 2333653 (Phase I), award amount $275,000
Period of Performance: Phase I: Dec 2023-July 31, 2024
NSF SBIR Phase II: "AI-Enhanced Career Assessment Tool to Accelerate Student and Professional Access to Emerging Technologies in Web3," awarded in 2025. Development and evaluation of an AI-enhanced career-assessment platform designed to accelerate student and professional access to emerging-technology careers, initiated in 2025 and currently in progress, with anticipated completion in May 2027.
Contract Number: 2450577 (Phase II), award amount $1,250,000.
Period of Performance: Phase I: Phase II: May 14th 2025- April 30th 2027

DeFi All Odds’ patent-pending dynamic recommendation algorithm could serve as a foundation for military decision-support systems that evaluate options, identify capability gaps, and recommend actions based on mission priorities, available resources, and operational constraints. Potential applications include personnel simulation, supply chain validation, helping installations prioritize backup power and water investments; supporting medical planners in comparing blood and medical-supply replenishment strategies; recommending training and sustainment pathways that allied forces can realistically maintain; and helping disaster-response teams determine where to position relief supplies and how to allocate limited resources. With additional development, the technology could also help assign support tasks among personnel, robots, and software based on their capabilities and need for human oversight. These applications would combine configurable recommendations with mission-specific data, simulation models, and validation methods to help military leaders compare trade-offs, test assumptions, and make better-informed decisions, while retaining human authority over consequential actions.
