C3 launches the Integrated Development Studio, a low-code/no-code environment for enterprise AI apps
C3, the leading enterprise AI software provider for accelerating digital transformation,introduced the C3 Integrated Development Studio (IDS), a low-code/no-code environment for developing, deploying, and operating enterprise AI applications.
IDS provides data ingestion, data modeling, machine learning feature engineering and model lifecycle management, and a metadata-driven UI development tool. The hybrid, multi-cloud distributed architecture of C3 IDS enables secure, highly available, and rapidly scaelable application development.
C3 IDS delivers an improved developer experience through a low-code/no-code environment that accelerates developer velocity, an important capability for building complex enterprise-scale applications on the C3 AI Suite. C3 customers have already built end-to-end applications for a wide range of use cases on C3 IDS, including predictive maintenance and yield optimization.
Based on recent analysis by an independent system integrator, building an application on the C3 AI Suite is at least 25x faster—and is typically 50x to 100x faster—than using existing cloud microservices.
“With C3 IDS, we rapidly developed and deployed a predictive maintenance AI application into production,” said Ryan Gross, a leader in the Machine Learning practice at strategic services and information technology consulting company Pariveda Solutions.
“The low-code/no-code environment provided well-integrated solutions for many of the problems we have spent great time and effort to solve in the past, from data integration and data modeling to machine learning and application development. Developing and deploying this application in a week would have been impossible without C3 IDS.”
First-of-its-kind AI application development platform
C3 IDS allows developers and data scientists to focus on solving business problems by providing a single integrated environment that abstracts routine and complex application development tasks, through four environments:
- C3 Data Studio: Ingest data of any kind and size through a browser-based interface; process, query, and plug the data into applications; connect to existing databases; define transformations; and develop or extend application objects (e.g., data model, analytics, algorithms, UI). Developers can also extend prebuilt industry and functional application packages to accelerate development.
- C3 App Studio: Develop analytics through a visual interface and a metadata-driven UI Designer to develop an application front end.
- C3 ML Studio: Manage prebuilt machine learning pipelines, machine learning model development, and hyper-parameter tuning. Integrate all popular machine learning libraries including TensorFlow, Keras, Scikit-Learn, and more, in composable AI/machine learning pipelines.
- C3 DevOps Studio: Access all essential DevOps functions including source control, continuous integration/continuous deployment as a fully managed service, resource monitoring, queue management, task scheduling, and more.
C3 IDS abstracts the complexities of hundreds of cloud platform services (e.g., AWS RDS, Amazon S3, AWS Kinesis, Azure Event Hubs, Amazon DynamoDB, Azure IoT Hub, Google BigQuery, Google Cloud ML Engine, etc.) and thousands of developer tools (e.g., Jenkins, Apache Maven, Puppet, GitHub, etc.) to allow developers and data scientists to focus on the business problem they are solving.
C3 IDS is fully integrated with the C3 AI Suite, allowing users of this low-code/no-code environment to collaborate seamlessly with users who prefer writing code.
“C3 has invested $500 million over the past nine years in building the C3 AI Suite, simplifying the ability to develop AI-based applications and reducing the underlying complexities,” said Ed Abbo, C3 president and chief technology officer. “Using the C3 AI Suite, a small team of developers and data scientists can build complex AI applications and roll out large-scale systems with efficiency and accuracy in just months. With C3 IDS, we have taken another step to speed the delivery and economic value of enterprise AI.”