C3 Marries AI and Low Code; Project Promotes Smarter Apps, Faster Delivery
Software firm C3 is marrying two of today’s biggest trends in app development – AI and low code / no code IDEs. The resulting platform allows developers and data scientists to work more closely together.
Software firm C3 is marrying two of today’s biggest trends in digital transformation apps – AI and low code / no code IDEs.
The result is the C3 IDS (Integrated Development Studio), a single integrated environment that abstracts routine and complex application development task. One of the main ideas is to create a unified platform that is designed to let developers and data scientists better work together and focus on solving business problems, according to Ed Abbo, C3 president and CTO.
C3 IDS runs atop the company’s already-available C3 AI Suite, which offers easy access to a rich set of services and capabilities via an intelligent abstraction layer. The C3 AI Suite offers simple access to a comprehensive set of services for data integration, data management, data processing, time series; AI and model management; and a robust security framework.
“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,” Abbo said in a statement.
C3’s approach does more than simply help app developers design a cool and smart low-code app. With an end-to-end approach, C3 IDS delivers a comprehensive set of capabilities for developing, deploying, and operating large-scale apps with AI, predictive analytics, and IoT features.
The goal, according to Abbo, is to enable companies to go from idea to launch as much as 25x to 100x more quickly than traditional approaches. Aside from simply combining AI and low code, C3 IDS does this using some innovative thinking and design work.
First, C3 IDS brings together four (4) crucial capabilities – or “environments” into a streamlined, intelligent app pipeline, Abbo noted. Among these environments are:
C3 Data Studio: Through a browser-based interface, users can ingest data (of any kind and size). Once the data is available, users can then process, query, and plug the data into their applications. On that note, users can manipulate this data through various key stages of a pipeline -- connect to existing databases; define transformations; and even develop or extend application objects (such as data models, analytics, algorithms, UI). Developers can also extend their apps with pre-built packages to accelerate app development.
C3 App Studio: Users can develop analytics through a visual interface and a metadata-driven UI Designer to develop an application front end.
C3 ML Studio: This allows for the management of pre-built ML (machine learning) pipelines, model development, and hyper-parameter tuning. Further, users can integrate many popular ML libraries (such as TensorFlow, Keras, Scikit-Learn, and more, in composable AI/ML pipelines.
C3 DevOps Studio: To fine-tune apps and propel a fast deployment time, users gain access to support for crucial DevOps functions. Among them: source control, continuous integration/continuous deployment as a fully managed service, resource monitoring, queue management, task scheduling, and more.
Second, Thanks to its compatibility with C3 AI Suite, developers using C3 IDS gain simplified access to hundreds of popular 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.), as well as thousands of developer tools (e.g., Jenkins, Apache Maven, Puppet, GitHub, etc.).
This combination of C3’s performant app pipeline and simple access to a rich services library is the recipe that promotes deeper and clearer collaboration between developers and data scientists that makes effective AI apps successful, C3 officials added.
As to use cases, Abbo reports that C3 currently supports the rollout of configurable, prebuilt, AI apps for predictive maintenance, fraud detection, IoT sensor and network health, supply chain optimization, energy management, anti-money laundering, and customer engagement.
One early C3 IDS adopter, Ryan Gross, a leader in the Machine Learning practice at IT consulting firm Pariveda Solutions shared his experience in a statement.
“With C3 IDS, we rapidly developed and deployed a predictive maintenance AI application into production. 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.” Gross said.
Beyond speeding up delivery of simple apps, bringing together AI with low-code can also have greater, long term impact. C3’s chief product officer Houman Behzadi, wrote in a recent blog that huge value is also derived by closing what C3 calls the “execution gap” between CxOs and IT – and putting these execs on the same page for tackling more long-term, strategic goals.
In part Behzadi said:
The gap between CXOs and IT starts to widen when the topic is newer technologies and capabilities like predictive analytics and machine learning. <
Part of this gap is due to the role IT plays. IT invests significant effort not only in keeping existing systems running but also evaluating and implementing new technologies. This leads to a scattershot and complex enterprise landscape with data in many formats in multiple databases and other sources.
I have seen this play out in organizations as they contend with digital transformation. Often the first attempt is a do-it-yourself (or, do-it-with-system integrators) approach. Many months, or even years later, they have little to show for the investment except brittle and complex systems. As a result, IT fails in tying disparate data sources all together—almost half of the respondents noted this in the Forrester research. That means digital transformation remains a mirage for many organizations—or typically death by a thousand proof of concepts.
A better approach—one that C3 customers know well—is to bring a cross-functional team that focuses on integrating multiple technologies on a single unified platform that can still access legacy systems and data and address new sources of data over time.
Behzadi also noted that a Forrester research study, commissioned by C3, noted that closing this ‘execution gap’ was a priority for both CxOs and IT.
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