Continuum Analytics


Custom programs and expert guidance to help connect your most important people to your most important data.

As leaders in scientific Python computing, Continuum specializes in solving large-scale technical computing problems with an emphasis on data management, analysis, and visualization. Backed by years of industry experience, Continuum’s highly-trained consultants provides consulting services for clients in energy, finance, defense, biology, medicine, and many other domains.

Continuum provides clients with innovative, effective solutions for even the most challenging of problems. We use an iterative development model in which our clients are an active part of the development process. Clients are able to work with the product as it is prototyped and refined, and provide regular feedback throughout the engagement. After the engagement, we enable internal staff to maintain and build upon the final product.

Web and Native Applications

Does your business depend on mathematical, scientific, or engineering workflows (machine learning, risk analysis, etc.)? Continuum consults with customers on User Interface (UI) design and build. We work with clients to build clean desktop/native and web applications. Web applications bring the same functionalities of desktop/native applications to a more accessible and collaborative web interface.

Optimization and Performance

Is your Python running fast enough? Continuum will work with you to optimize the code running on your existing infrastructure and to leverage any available cores, machines or GPUs to get the best solution for your company. Often speedups of several orders of magnitude are achieved. ("Continuum helps speed up Python program 114,000 times")

Big Data Insights

Do you have a lot of data, but you’re not sure where to start? Continuum works with companies to expose real world insights from large-scale data sets. Experienced in many different industries, Continuum understands the intricacies of advanced analytics and helps you to understand, manage, and derive value from your data.

Other areas of focus include:

  • Upgrading and managing enterprise Python deployments
  • Migrating existing infrastructure to newer systems
  • Building richly interactive visualizations for data exploration
  • Designing UIs and interactive visual dashboards for analysis and reporting
  • Optimizing infrastructure to analyze data and derive value
  • Building management systems to streamline data analysis
  • Creating vectorized and array-oriented computing systems
  • Setting up parallel and scalable computing on clusters
  • Designing performance-aware algorithms

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