What We Do?
We help Institutions improve their Outcomes through the use of Machine Learning and Quantum Optimization or Simulation under a Hybrid Model. Using our versatile “Financial Services Operating Layer” that sits on top of Quantum Cloud, seeks to solve NP Hard, intractable and computationally intensive optimization and simulation problems.
Financial Services Operating Layer
Our versatile “Financial Services Operating Layer” sits on top of Quantum Cloud to solve NP Hard, intractable and computationally intensive optimization and simulation problems. CogniFrame uses a combination of Machine Learning techniques (GAN, qGAN, Neural networks, Decision Trees, etc.), Risk Modeling and proprietary problem reformulation and pre-processing to deliver solutions that are Pure Quantum, Hybrid Quantum or Near Quantum.
We solve multi-period stochastic optimization problems using a Hybrid Classical+Quantum model. Our algorithms leverage the power of Quantum Computing to derive optimized solutions that address a number of long held problems especially related to Financial Services including NP Hard problems, sampling, etc., to help Financial Institutions improve their Outcomes. Our focus is on hybrid solutions for early commercialization.
Simulations are a difficult computational problem due to its scale and complexity. Using proprietary methods, CogniFrame is able to handle problems up to a certain scale using Quantum Simulation techniques providing a ready path to commercialization as Qubit availability increases.
Why Choose us?
Innovative Hybrid Solutions that combine Classical approaches with the power of Quantum.
Research based Solutions
Our solutions are based on research experiments and pilots with live data. We provide Quantum, Hybrid Quantum and Near Quantum options where feasible.
Easy to Implement
Simple API’s and we can work with raw data as well.
Privacy Protected, Secure Solutions.
Read about Machine Learning and Quantum Advances, tools and more.
CogniFrame featured on Finadium, the Securities Finance Monitor. Read more about the article here.
Congratulations to our collaboration partner Toshiba on their release of the upgraded algorithms for SBM. The algorithm is also published in Science Advances. Read more about the article here.