Portfolio CH is SQT's production-grade quantum portfolio optimization platform — currently at Technology Readiness Level 5, live-benchmarked on real financial market data. It is both the first commercial product and the architectural blueprint replicable across every target vertical.
Institutional portfolio construction with cardinality constraints, turnover limits, sector caps, and realistic transaction cost models is a combinatorial optimization problem. Classical solvers trade off solution quality against wall-clock time — and at scale, both degrade.
Quantum annealing maps natively to the Quadratic Unconstrained Binary Optimization (QUBO) structure underneath these problems. Portfolio CH is the operational bridge between that mathematical fit and the decisions portfolio managers actually make every day.
Portfolio CH is built for institutional environments: auditable, regulated-market-ready, and architecturally replicable across verticals. Every component is production-grade, not a demonstration.
Portfolio CH is not merely a product. It is SQT's proof of industrialization — validating the proprietary QUBO libraries on real-world data, codifying reusable optimization templates, and establishing the architectural blueprint replicable across energy, logistics, pharmaceuticals, and supply chain.
Every component of Portfolio CH generalizes. The QUBO generation engine that maps portfolio constraints maps equally to grid balancing constraints; the multi-solver routing that optimizes compute for finance optimizes identically for logistics.
Portfolio construction, rebalancing, derivatives hedging optimization, stress-testing under scenario ensembles. First institutional pilots targeted within 12–18 months post-SPAC close.
Day-ahead and intraday dispatch optimization for renewable-heavy grids. Commodity arbitrage across volatile spot markets. Multi-node transmission planning.
Vehicle routing, warehouse slotting, multi-echelon inventory placement. Container port scheduling. The travelling-salesman family of problems at industrial boundary conditions.
Molecular conformational search. Protein-folding heuristics. Factory-line reconfiguration. Real-time scheduling at the edge of what classical solvers can compute in wall-clock time.