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Vishal Sikka Raises $50 Million For His AI Startup Vianai From Undisclosed Investors


Vishal Sikka Raises $50 Million For His AI Startup Vianai From Undisclosed Investors

Vianai vishal sikka


Vianai vishal sikka

Former Infosys chief Vishal Sikka's startup Vianai has reportedly raised $50 million as seed funding from undisclosed investors. Sikka demonstrated a new AI platform vision last week during his keynote address at Oracle Open World. Vianai's vision is to enable every company, in every industry, to utilize the explorable and explainable AI techniques.



"Companies today have been formed and reshaped by the systems of yesterday," said Sikka. "In the early days of personal computers, there were systems of record, then came systems of engagement. Today, we have the opportunity to create systems of intelligence that can bring AI techniques to transform all aspects of a business, and do so in a way that is transparent, explainable and explorable, inclusive and accessible to a massive number of developers. The Vianai platform helps us deliver on the promise of AI for every business and for all of us."

At the Oracle Open World, Vianai's demo showcased a fully integrated and exploratory experience for building and deploying many AI projects per enterprise and many experiments per project, where each element of an experiment — data, feature, model and results — can be introspected, modified, and reused for sharing and ongoing experimentation. A key advance in the Vianai platform is an innovative domain specific language for data science and machine learning that allows any person who can write a standard mathematical expression to fully implement all aspects of an algorithm (models and parameters) in a highly simple, succinct and fully implemented, explorable specification.

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Vianai's support for rapid exploration of the relationships between data, features, model and results, is joined to a highly visual design experience that will enable users to define and run dozens of experiments in the time it now takes to iterate through just one. In contrast to approaches such as AutoML, the platform ensures far better collaboration and alignment between data science practitioners and business stakeholders, ensuring that AI projects meet their goals.



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