The Extinction Event in Software is Upon Us

We believe all applications will need to become intelligent or they will cease to exist.

We don’t find very many dissenters. What we do experience is the question of how those applications will evolve into intelligent applications.

There is no single answer. As a result, we have exposed multiple ways to create intelligent applications, inject intelligence into existing applications, or to simply buy intelligent applications off the shelf.

Symphony AyasdiAI exposes a number of interfaces or applications to support this mission:

  • Python SDK
  • An application development framework for non-technical users.
  • A library of existing applications that can be customized for an enterprise’s specific needs.



For any such platform, where the bulk of the processing is performed on cloud or on-premise servers, it is imperative that access controls and requests are bounded tightly. A REST interface is a standard requirement for such tasks. To that end, we provide a RESTful interface that can be authenticated, queried upon and initiate jobs that require machine intelligence. Our RESTful interface is exposed from an API Server that utilizes Kong which then communicates with the underlying interfaces that are written in Java or C++

Python SDK

While having a RESTful interface allows an easy invocation of the libraries and methods available within the platform, it is at times necessary to work within the ecosystem that MI users are familiar with. Python is growing as the de facto language for Machine Learning and numerical computations, courtesy of the excellent Sci-Kit Learn and NumPy packages. Additionally, the ecosystem allows for integration with a number of packages and tools that allow easy access to virtually any system out there. With this in mind, we have focused on making available a Python SDK package that users can leverage to develop mission-critical solutions while using a familiar ecosystem.


While the REST API and the Python SDKs are key parts of an application strategy, Symphony AyasdiAI went one step further, developing a framework for accelerating the development of intelligent applications by allowing a far larger group of “data aware” resources to design and deploy these next-generation applications.

Envision addresses the gap between data science, IT and the business. Intelligent application development is often a disjointed, iterative and plodding process. Some resources had ML experience, others, data experience, others with business experience and yet others with development and deployment experience. The challenge was getting all of those people on the same page. It was difficult at best, so much so that many organizations did the natural thing – default to the familiar – powerpoint, excel or .pdfs.

Envision changes that process by providing simple Python, pre-built UI libraries, collaboration features, and AI platform connectivity, enabling more parts of the organization to create intelligent applications.

Now business analysts that understand analytic workflows can collaborate live with business owners and have their work checked by data science.

Application Library

Where Symphony AyasdiAI sees large, repeatable problems we will build those applications.

Anti-Money Laundering

Find subtle patterns hidden across multiple data types, including unlabeled data to significantly reduce false positives without increasing the risk profile.

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Clinical Variation Management

Understanding and managing clinical variation is foundational for any effort to deliver better care at lower cost.

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Population Health

What is profit today may very well be cost in the future making the prediction of population health one of the most critical capabilities in healthcare.

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Regulatory Risk

The defining feature in building regulatory risk models isn’t speed or even accuracy – it is transparency. Find out how to have all three.

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Develop a deeper understanding of complex denial groups to address the persistent challenges associated with denied healthcare claims.

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Counter Fraud

Fraud evolves and so should systems designed to detect it. Find and understand new types of provider, lab and patient fraud.

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