Tagup | AI for Logistics Decision Advantage

AI for Logistics Decision Advantage

Precision deep-strike capabilities, persistent surveillance, and low-cost autonomous systems make centralized depots and predictable supply routes high-value, low-survivability targets. The future fight demands greater logistics velocity, distributed sustainment, and plans that can re-prioritize continuously. The future fight demands decision advantage.

Tagup is a defense technology company founded at MIT that is delivering logistics decision advantage with next-generation AI. The company's AI-powered Manifest® decision engine simulates and optimizes logistics courses of action under real-world constraints and uncertainty, sustaining readiness in contested and degraded environments. A trusted partner of the U.S. military, Tagup supports logistics operations across supply, maintenance, and mobilization, including active deployments with aviation and medical logistics units.

Manifest: The Logistics Decision Engine

Manifest® is a logistics decision engine that combines human expertise with next-generation AI to keep forces supplied, maintained, and mission-ready on the contested modern battlefield.

Manifest first unifies siloed logistics data with the knowledge of domain experts to build a living world model of the logistics domain. It then uses proprietary Generative Reinforcement Learning™ to simulate outcomes across millions of possible futures and recommend the best course of action under real conditions and constraints. With Manifest, planners and commanders get the decision intelligence they need to quantify risk, anticipate disruption, and direct every constrained resource towards the decisions that move readiness most.

Operators navigate the decision loop with Argus®, Manifest's conversational AI interface. Operators express their requirements in natural language; Argus then translates those requirements into objectives and constraints, and returns auditable, executable courses of action with tradeoffs explained in mission terms.