In fast-paced industries like retail, logistics, telecom, and manufacturing, setting the right prices and negotiating smart contracts can be the difference between profit and loss. Yet, pricing and contract decisions involve countless variables: cost fluctuations, customer behavior, competitor moves, and market regulations.

The Challenge:

• Traditional pricing models rely on rules of thumb or historical data

• Contracts are often negotiated manually, leading to inconsistencies or missed opportunities

• Multiple objectives conflict (profit vs. volume, loyalty vs. margin)

• Pricing optimization becomes too complex as the number of products, regions, or clients increases

Quantum-Inspired Solution

Multi-Objective Optimization

HessQ models pricing and contract terms as a QUBO problem, balancing variables like revenue, volume, discount thresholds, and risk tolerance.

Rapidly tests thousands of "what-if" contract or pricing scenarios to find the best outcome — for both business and client.

Continuously adjusts recommendations as costs, customer behavior, or market conditions change.

Real-Time Deal Simulation

Adaptive Strategy Refinement

The Results:

• +15–25% increase in margin without losing customers

• Deals closed 40% faster through optimized contracts

• Improved pricing fairness and consistency across channels

• Reduced pricing errors and discount abuse