Why you should care?

Graphs are some of the most common objects in modern business - from data relations, human networks, roads, manufacturing lines, even images and text - almost all data is graph data.

However, interconnected data is notoriously difficult to analyze, due to its size and complexity. Quantum computing offers a cost-effective, fast and accurate alternative to traditional graph analytics. We develop enterprise applications for graph data processing on quantum computers, which are scalable, future-proof and modular.

Our Approach

Our 5-step research-based development framework for getting the maximum value out of your interconnected data.

  1. The business case

  2. Constructing graph data

  3. Quantum graph neural networks through sparse matrix analytics

  4. Execution reports and classical benchmarking

  5. Enterprise integration and automation

The approach is adapted to each use case and each industry, based on initial data.

1. The Business Case

The most important part of any quantum application is the business impact. We typically begin the project by performing a comprehensive analysis of the economical impact of quantum applications, risks, long-term outlook and interdependencies (especially on hardware), to design the project implementation and software solutions which solve actual business problems.

  • Economical impact

  • Risk assessment

  • Long-term outlook and hardware interdependencies

2. Constructing Graph Data

Interconnected data in corporations is typically structured in one of two ways:

  • Interconnected data not yet in graph format: Most prominently, relational databases naturally have connections between different data points, and can efficiently be analyzed using graph analytics and graph machine learning. We turn your data (in whichever format) into graphs, to run analytics on.

  • Graph data: In case your data is already structured in a graph format (e.g. network data, transportation data, process data, etc.), we work with you to optimize the format for quantum analytics and prepare it for further analytics.

3. Quantum Graph Neural Networks Through Sparse Matrix Analytics

Graph data can be efficiently encoded and analysed using sparse matrices (matrices where almost all entries are zero). Quantum algorithms outperform classical in performing operations on such objects and are perfectly suited for their analysis. We develop proprietary, highly specialized and performant algorithms for graph analytics and graph machine learning based on operations on sparse matrices.

4. Execution Reports and Classical Benchmarking

Our goal is always the same: Push the state-of-the-art and improve over classical models. We want to build the best classical algorithms and then beat them with quantum. We will either develop own classical machine learning models, or benchmark our quantum models against current classical ones. Sometimes the best solution turns out to be a mix of both.

5. Enterprise Integration and Automation

Integration solutions in all parts of the data analytics pipeline:

  • Input data integration

  • Data engineering and preprocessing

  • Quantum encoding

  • Data processing

  • Backend integration with HW providers

  • Reports and business application integration

  • MLOps

How we can help

We have an expert team to help you with building quantum analytics on interconnected data, including identifying use cases, development of quantum algorithms and training.

See our Solutions

Unlock the power of quantum for interconnected data analytics

ML Models

Monte Carlo

Speed up your analyses and reduce costs.

Tools

Optimization

Faster and more effective logistics, manufacturing, planning

Predict

Predict

Analyse trends and precedict movements from data.

Understand

Understand

Perform contextual segmentation and structural analytics.

Operate

Operate

Unlock interconnected organizational data to drive performance.

Build

Build

Use analytics of interconnected data to build better products.

Classical-quantum solutions for immediate results.

We develop hybrid classical-quantum algorithms which function both on classical and quantum backends. This allows your applications to be executed today, while benefiting from quantum in the long term as the hardware matures. Our proprietary interpolators automatically adapt computing capacity on classical and quantum backends based on the state of technology.

Contact us for a free discovery workshop

We will evaluate opportunities for implementing quantum on interconnected data in your organization and assess potential applications to your business.

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