C3 AI, the Enterprise AI application software company, announced that C3 AI Ex Machina, its no-code solution that anyone can use to generate actionable enterprise AI insights, has seen significant growth in its first full quarter of release. More than 25 organizations and companies are now generating predictive insights and reaping the benefits that no-code enterprise AI provides, including energy giant Con Edison, healthcare leader Stanford Medicine, and the HIVE Lab at George Washington University.
Today, organizations are actively working to better understand how they can apply the power of enterprise AI to deliver predictive insights and improve business outcomes. As the only complete no-code AI/ML solution, C3 AI Ex Machina enables analysts, operators, and subject matter experts to develop, scale, and apply enterprise AI insights without the computer and data science background typically required to develop complex code for AI-based applications. C3 AI Ex Machina’s easy to use, yet extensive capabilities, provide users with the tools they need to quickly ingest and prepare petabytes of data, construct precise ML models with AutoML, and generate actionable insights and applications they can deploy across their organization. The product also allows individuals, teams, and organizations to collaborate and scale with confidence using the C3 AI Suite – a tried, tested, and proven end-to-end enterprise AI platform – to apply the power of predictive analytics against digital transformation initiatives.
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Since its January 2021 launch, C3 AI Ex Machina customers are deriving insights across a diverse set of industries and use cases, including medical research, sales forecasting, international trade analytics, patient care, marketing analysis, and more.
C3 AI has continued to expand and enhance the features and capabilities offered in C3 AI Ex Machina, with innovations in AutoML and feature transformation. And, with the release of Version 7.20 of the C3 AI Suite in May 2021, C3 AI Ex Machina has further improved the user experience, with additions such as multiple cross validation methods, new feature engineering nodes to improve model results, a canvas mini-map, and a searchable templates page. New save and load data nodes enable users to automatically save and version analysis and input/output data, allowing experiments to be reproducible. In addition, users now have access to a new Splunk data connector, along with a comprehensive set of existing connectors for popular data stores such as Snowflake, SAP, AWS S3, Azure Data Lake, Oracle, Salesforce, and others.
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“C3 AI Ex Machina empowers anyone to apply the predictive power of enterprise AI to their work. As a Bioinformatics Lab, we are always looking for additional avenues to complement our biomedical expertise with advanced data science techniques,” said Stephanie Singleton, Section Lead for Microbiome Research with the HIVE Lab at the George Washington School of Medicine and Health Sciences. “Our team was able to easily integrate previously developed models into the C3 AI Ex Machina environment and improve those models through its AutoML capabilities, robust model evaluation metrics, and user-friendly interface. C3 AI Ex Machina has allowed us to scale our work in predictive intervention and treatment selection for patients with epilepsy and diabetes, and we’re excited to continue our partnership with C3 AI to drive better patient outcomes.”
“We’ve been incredibly pleased with the uptake and interest C3 AI Ex Machina has generated since its official launch earlier this year,” said C3 AI President and CTO Ed Abbo. “More and more organizations have discovered the incredible value enterprise AI-powered insights can deliver, and C3 AI Ex Machina’s no-code approach represents the fastest and simplest way for anyone to start surfacing those insights to generate improved business outcomes.”
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