The C3 AI Platform software uses a model-driven architecture to accelerate delivery and reduce the complexities of developing enterprise-scale AI applications. Independent studies have shown that the C3 AI model-driven architecture reduces the amount of code developers need to write and maintain by 99% and decreases the effort required to develop and deploy AI applications by a factor of 26 compared to traditional “structured programming” approaches.
Enterprise AI applications typically require numerous underlying elements – such as data persistence services, data streaming services, messaging services, analytics services, machine learning services, security services, and dozens or hundreds more. With a traditional structured programing approach, developers must devote significant time and effort in writing extensive code to define, manage, connect, and control each element. This results in overwhelming complexity and highly brittle applications that can break any time an underlying element is changed or updated – a primary reason why the vast majority of enterprise AI efforts fail.
By contrast, the C3 AI model-driven architecture provides an “abstraction layer,” that allows developers to build enterprise AI applications by using conceptual models of all the elements an application requires, instead of writing lengthy code. C3 AI provides thousands of pre-built conceptual models that can be easily modified and extended, and developers can efficiently create their own models as well. These prebuilt, extensible models encompass a vast range of entities, including business objects (customer, order, contract, etc.), physical systems and subsystems (engine, boiler, chiller, compressor, etc.), computing resources and services (database, stream processing, etc.) – anything at all that an application requires, can be represented as a model in the model-driven architecture. To ensure ongoing operability of C3 AI’s thousands of prebuilt and extensible models on different underlying infrastructure (e.g., AWS, Azure, etc.), C3 AI runs ten’s of thousand’s of automated tests and security scans any time a change or update is made to the infrastructure.
The model-driven architecture enables the use of “declarative programming,” an efficient approach that essentially allows programmers to specify what they want the application to do, without having to write explicit code on how to do it. Compared to traditional structured programming, the model-driven architecture and declarative programming shorten time to value and reduce total cost of ownership. Leveraging this model-driven architecture, application developers and data scientists can focus on delivering immediate value, without the need to manage the complexities of the underlying elements. These conceptual models can also be used by many applications, further accelerating development of new applications.
The C3 AI Platform’s model-driven architecture serves as an object-centric abstraction layer removing complexities and barriers across developers, data scientists, and business end users.
The C3 AI Platform and its model-driven architecture enable application developers and data scientists to focus on delivering immediate value, without the need to learn, integrate, or understand the complexities of the underlying systems.