C3 AI and DataRobot are both leading AI cloud platforms. But which one is best for your business?
C3 AI and DataRobot are two of the leading AI cloud platforms. As such, this is a close comparison. Each has an extensive set of artificial intelligence features. Which is best for your company? Let’s review the key features and compare them.
So what is an AI cloud platform? AI cloud platforms provide artificial intelligence (AI) and machine learning (ML) capabilities that are structured to simplify the process of analyzing data, finding patterns, and build models. In essence, they support anything that a data scientist wants to achieve with data analytics. The platforms also seek to broaden the scope of this technology to make it available to business analysts, software developments, enterprise architects and IT operations teams.
Forrester Research lists the key capabilities in this sector:
Also see: What is Artificial Intelligence
The C3 AI Application Platform uses a model-driven architecture to accelerate delivery and reduce the complexities of developing enterprise-scale AI applications. It includes C3 AI Studio, a library of deep-code tools and a low-code environment for developing, deploying, and operating AI applications.
The idea behind it is to provide a cohesive development experience for data ingestion, data modeling, machine learning feature engineering, and model lifecycle management. It incorporates metadata-driven UI development tooling. Users can explore, clean, contextualize, and label data, as well as visualize data pipelines and develop features through an integrated code experience. This is said to reduce the effort required to move data pipelines into production
C3 AI has thrown its hat into the Google Cloud ring in a big way. Most of its announcements this year are about their partnership to accelerate joint selling and co-development efforts with Google Cloud. C3 AI’s entire portfolio of enterprise AI applications is available on Google Cloud.
They are working together on a go-to-market strategy to expand pilot programs with Fortune 2000 companies, as well as jointly develop AI-driven applications using Google Cloud’s Vertex AI, ML capabilities, and data analytics services. All of C3 AI’s 42 enterprise AI applications have been optimized for Google Cloud and are available on the Google Cloud marketplace.
DataRobot AI Cloud is a machine learning platform for automating, assuring, and accelerating predictive analytics. It helps data scientists and analysts to rapidly build and deploy accurate predictive models in a fraction of the time required by other solutions. It can visually track prediction progress with charts and manage workloads and delays. This enables users to view which predictions are delayed, why they are delayed, and the time frame.
Another key DataRobot feature enables users to compare data drift across multiple features (or groups of features) as well multiple time periods. This can be done for both training and scoring data. Available in the cloud, there is also a managed version known as DataRobot Dedicated Managed AI Cloud. This dedicated hosted version of AI Cloud is managed by DataRobot experts to support AI and machine learning projects with the advantage of public cloud services. This reduces cost and time-to-value in deploying, upgrading and managing the AI infrastructure.
Who wins? C3 AI provides much of the features that are available from DataRobot. In addition, it has natural language processing (NLP) and stronger statistical and mathematical tools. C3 AI wins as a slightly broader AI cloud platform.
Also see: Top AI Software
C3 AI provides plenty of autocomplete and recommended suggestions to help users create models and built AI apps. Users can instantly check for errors on data model construction and function implementation with each file save. Further usability features include being able to hover over any keyword, data model element, or function to receive in-context documentation.
Users can click into references and implementation files with the code to traverse across an application and its dependencies. Additionally, they can generate test files specific to data model elements and APIs or individually run test files or group multiple tests together and run them in sequence or in parallel.
DataRobot AI Cloud, too, comes with plenty of automation bells and whistles to take the time out of mundane data science and model creation operations. It can run on any combination of public clouds, data centers, or at the edge. Users like its governance and data protection capabilities.
DataRobot AI Cloud’s single-platform approach serves data scientists, analytics experts, IT, and the business with a single view of all data from any source, any type. Users comment that it’s simple to use and adapt to your own needs. It is also said to be quick, easy to use, and effective at building models of most types.
Automation eliminates much of the coding work. DataRobot automates model setup, testing, and administration. Models can be built from any data source including tables and plain text, as well as graphic and geographical data. But there are a few negative comments, too. Sometimes the tools to decipher results are not the most user friendly, and there can be a lack of flexibility. Some say it favors modeling quantity over quality in some scenarios. And others complain that there are so many options that it can be difficult to know what to choose. One user said he wanted it to be easier to upload and integrate massive datasets.
Overall, though C3 AI offers more comprehensive support such as 24/7 live support and plenty of online options. Support from DataRobot is limited by comparison, primarily via online resources. Similarly, C3 Ai offers a wider range of documentation and training than its rival. DataRobot doesn’t yet offer live online and in person training.
In terms of usability and support, C3 AI wins.
Also see: Top Business Intelligence Software
Both platforms are used heavily by data scientists and developers. C3 AI Studio enables developers and data scientists to focus on solving complex business problems by providing an integrated environment that abstracts routine and complex application development tasks.
It provides technical users with core code-based experiences through extension of the Visual Studio Code source-code editor. Developers can use it to leverage out of the box auto-suggestions and autocompletion across models. Similarly, data scientists can write custom Python methods and inspect any issues in their logic using an integrated Python debugger, and QA engineers can manage test files across multiple applications.
Another C3 AI feature, on-demand JupyterLab Notebooks, provides an interactive interface to all data and machine learning services. Users can also import libraries from public or private repositories to train models and explore data, or utilize the tools and libraries in place such as JavaScript, React, and SCSS. They can then configure continuous integration (CI) pipelines, inspect the qualities of build artifacts, and deploy builds into production.
DataRobot makes it easy to use open-source modeling techniques from R, Python, Spark, H2O, VW, XGBoost, and more. Small data science teams can use it to build and deploy a great many models. Instead of having to laboriously create each one, it acts as a productivity multiplier. Its library of algorithms and pre-built prototypes is useful for feature extraction and data preparation. Automation makes it possible to select and combine multiple algorithms to produce more accurate predictive models. It incorporates data science best practices. The platform enables analysts and others to perform data scientist-like modeling tasks that previously required a high level of skill.
There is little to differentiate between these two platforms in this category, but the laser focus of DataRobot on data science gives it an advantage.
The most recent Forrester Research analysis of AI/ML platforms places C3 AI slightly ahead of DataRobot, although both are classified as Leaders. Forrester is especially enamored by C3 AI’s vision for enterprise AI, presumably influenced by its close relationship with Google Cloud. In the eyes of the analyst firm, this gives it a big edge in terms of gaining market share and enhancing its popularity.
“At a time when most vendors focus on tools for data scientists, C3 AI has always envisioned a platform approach to AI,” said Forrester analyst Mike Gualtieri. “Ahead of its time, C3 AI’s strategy is to make AI application-centric by building a growing library of industry solutions, forging deep industry partnerships, running in every cloud, and facilitating extreme reuse through common data models.”
DataRobot is also well-regarded by Forrester. The analyst firm said its customers, “appreciate the company’s rise from a niche automated machine learning (AutoML) player to a full-lifecycle AI platform.”
Strengths are listed as tooling and functionality in data preparation, model evaluation and explanation, ModelOps, and application building. It has gained ground recently by being able to augment and enrich data for modeling and adding a plug-in framework to make it easy for partners to add platform capabilities. Forrester said it has a relatively low barrier to entry for those adopting the platform and users commented on its ease of use and model documentation.
“DataRobot is a solid option for enterprises that want a platform that has tooling for extended AI teams while simultaneously providing collaboration and scale to manage existing use cases and crank out new one,” said Gualtieri of Forrester.
On Gartner Peer Reviews, though, DataRobot is well-featured and C3 AI is entirely absent. No one has reviewed it. Thus, there could be maturity issues still to be ironed out. Forrester graded DataRobot ahead of C3 AI in number of customers and company size. But otherwise, C3 AI came out ahead in inferencing, applications, data, architecture, vision, and marketing. They receive the same grade on performance.
With C3 AI slightly ahead on Forrester, but with no presence at all in Gartner Peer Reviews, this one is a tie.
Also see: Top Natural Language Processing Companies
There is a slightly different emphasis between both platforms. C3 AI is more aimed at organizations that want to build, deploy, and operate enterprise AI applications. DataRobot concentrates more on serving data scientists who are looking for a deep learning solution.
But that characterization is an oversimplification. C3 AI also does a good job looking after the needs of data scientists. And DataRobot has plenty of features to help organization build and run AI apps. But that overall emphasis does play a role in the final choice of platform.
Forrester scored them both as Leaders so either one would be a good choice. The analyst firm sees a brighter future for C3 AI. “If the company can accelerate industry partnerships for both solutions and go-to-market, it could become the de facto AI platform standard for the world’s most complex industries.”
In summary, opt for DataRobot if you want to arm data scientists with a great AI platform. But if you are looking for an AI platform with a wider base, C3 AI appears to have broader applicability.
Also see: The Future of Artificial Intelligence
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