The Wolverine Group has spent years helping federal teams understand noisy information environments. Now it is applying the same habit to a quieter problem: how government actually buys, teaches, and uses AI without surrendering judgment.
Fairmarkit started with the corporate purchases too small and tedious for anyone to love. Now its AI agents run sourcing work from intake to award - and customers say the bigger prize is not merely savings, but time.
DeepVu (legal entity Vufind Inc.) is a San Ramon, California startup building AI planning agents for supply chain teams. Its platform pairs a supply-chain knowledge graph (VuGraph) enriched with macroeconomic and trade signals, a digital-twin simulator (VuSim), and reinforcement-learning decision agents (VuDecide) to make demand planning, inventory, procurement, production and logistics decisions more resilient to shocks - while trimming cost and carbon. Founded in 2016 by Moataz Rashad and Prof. Walid Aref, the company pivoted from computer-vision roots to focus on autonomous, shock-resilient supply chain planning for manufacturers and retailers.