Icosa Computing

Icosa Computing is a New York City-based startup founded in 2022 by Mert Esencan, applying quantum computing research to solve large-scale discrete optimization problems in finance. The company's origins lie in quantum computing and statistical physics, with a team of physicists and computer scientists developing core scheduling and optimization techniques from studying combinatorial Ising machines and quantum-inspired algorithms. Rather than experimental quantum applications, Icosa uses accessible annealing-based methods compatible with current technology. Their proprietary Dynamical Parameter Selector (DPS) creates optimal combinatorial models for use cases from risk-minimized profits at funds to improving LLM reasoning accuracy in regulated industries. Icosa has optimized portfolios with over 25,000 equities—beyond what's possible with classical solvers. The company raised $50K from ScaleX Ventures, Duality Accelerator, and Creative Destruction Lab, with support from University of Chicago, UIUC, Chicago Quantum Exchange, and Argonne National Laboratory.