The Virtual MemComputing Machine, available as a SaaS platform, solves the largest and most complex industrial computations associated with optimization, big data analytics and machine learning. Proven to deliver the performance of quantum computing today, our clients are using MemComputing to solve problems that are impossible given classical or quantum methodologies.

Virtual MemComputing Machine Workflow


Leveraging Our Disruptive Technology

Our proprietary Virtual MemComputing Machine (VMM)
is currently available in a Software as a Service platform, enabling the mathematical programming technology of our VMM to dramatically reduce costs, improve operational efficiencies, and increase profitability for our clients.

Start solving your hardest problems today, register to become a free Beta Tester!

Our Solvers


Integer Linear Programming



Available for Demo


Quadratic Unconstrained Binary Optimization

Available for Demo


Maximum Satisfiability

Available for Demo

Integer Linear Programming

The Virtual MemComputing Machine is an Integer Linear Programming Solver engine that is currently being used to solve industry’s most complex optimization problems. Clients have the choice of using a user interface to upload and run problems or an easy to integrate application programming interface (API) to integrate the service with their own systems.

ILP Optimization Modes

This mode allows users to extract near optimal sets of parameters for a given problem through its fully automated Markov Chain Monte Carlo algorithm, and returns the parameter distributions along with the best objective and variable assignments found.

Users can then apply these parameters to the Standalone Solver and the Dynamic Solution Search to improve the solution of the problem. The parameters found are typically considered “good” for problems similar in structure or nature, and can be used as starting parameters or boundaries in the Dynamic Solution Search mode.

This mode represents the most basic usage of our Virtual MemComputing Machines. The purpose of this mode is to use the Markov Chain Monte Carlo algorithm to search for the optimal parameters to improve solution search.

If no optimal parameters ranges for the problem are known, the Dynamic Solution Search provides a tool to dynamically tune parameters while simultaneously improving solutions to the problem.

Users select this mode for a single MemCPU run. Whether it be to test a specific set of parameters or a known optimal set of parameters, this mode returns the number of unsatisfied constraints and objective versus time, as well as the best objective and variable assignments found.

Coming soon! This mode will be able to predict the suitable parameters for a user’s problem and test them in a single run. 

Our ILP Solver Supports

Easy to Use

File upload for manual testing

Binary & Integer Variables

(Continuous variables coming soon)

ILP Problems

As .MPS or CPLEX’s .LP files


Accelerated instances

Supported Modeling

and Programming Languages





*Will work with you on other automation/interface needs*

Learn More About Our Technology

Professional Support

Here at MemComputing, your experience is our number one priority. Customers receive support from our optimization experts who are ready to help at a moment’s notice.

Contact us directly at [email protected] for additional assistance.