When every performance
improvement counts
Fast.
Accurate.
Flexible.
Scalable.
We Have Solutions for Any
Industry or Business
Finance
Boost return and decrease risk in critical financial challenges, such as:
- Portfolio management
- Trading optimization
- Risk management
- Financial planning and budgeting
Manufacturing
Revolutionize your production, assembly, and storage to increase productivity in your factories and warehouses:
- Resource allocation
- Scheduling
- Assembly line balancing
- Facility layout optimization
Logistics
Improve decisions to maximize efficiency & reduce costs in your day-to-day operations:
- Vehicle routing
- Warehouse optimization
- Supply chain optimization
- Scheduling and dispatching
Our platform continues to compute when others hit a wall
LightSolver’s groundbreaking platform utilizes the speed of light, concentrating the power of thousands of computers into one desk-sized device and still outperforming industry leaders. Taking on the “3-Regular 3-XORSAT Challenge,” LightSolver solved the problem in polynomial time, while all other state-of-the art classical and quantum computers solved it in exponential time.
Feature Selection
(L0 REGULARIZATION)
The ultimate goal of any sparse coding method is to accurately recover an unknown sparse vector from a few noisy linear measurements. LightSolver developed a quantum-inspired algorithm for the most general sparse coding problem as a quadratic unconstrained binary optimization (QUBO) task and challenged a leading deep learning solver. We conducted numerous experiments with simulated data on our platform to demonstrate its advantage over baseline methods. We have reached accurate (ground-state) solutions compared to a state-of-the-art machine learning algorithm. Our method has proven less prone to errors than competing solutions.
Reaches an accurate solution even if you have more relevant genes.
Faster than
TensorFlow
We trained a neural network for 30 minutes to solve five problems from the MAXSAT Evaluations contest. Experiments on benchmark data sets show that LightSolver achieves significantly lower time-to-optimal-solution compared to a state-of-the-art deep-learning algorithm, where the gain in performance tends to increase with the problem size. Benchmarked against a TensorFlow, LightSolver achieved up to x1000 faster time-to-optimal solution.
