Written by 9:24 am Generative AI

### Transform Data Into Knowledge Using Generative AI

The platform is designed to enable natural language interactions, making it easier for users to que…

The impact of generational AI is swiftly transforming various aspects of our lives, particularly influencing the realm of data control and security. Cohesity, a company specializing in AI-driven data management and security solutions, introduced Cohesity Gaia to leverage generative AI in a unique manner, enabling customers to interact, analyze, and derive value from their data repositories.

The Core of Cohesity Gaia

Cohesity Gaia serves as an AI-powered conversational research assistant, intertwining Big Language Models with an organization’s specific data to provide a platform for users to engage with and extract insights from their data assets. This innovative platform facilitates natural language interactions, allowing users to query their data seamlessly without the need to navigate complex databases or understand intricate query languages.

At the heart of Cohesity Gaia lies generative AI, enabling verbal exchanges with data where users can engage in dialogues, pose questions, and receive contextually relevant and precise answers, departing from the traditional method of sifting through data or directories.

The platform employs Retrieval Augmented Generation to furnish responses deeply rooted in the organization’s unique data landscape, offering tailored insights rather than generic information.

Data Transformation into Actionable Insights

In a conversation with Greg Statton from the Office of the CTO – Data & AI at Cohesity, an early adopter customer working in materials innovation shared positive feedback about the device. She highlighted how scientists worldwide swiftly embraced the tool, impressed by its ability to render their data interactive.

Often likened to the “new oil,” data requires refinement to unlock its value, akin to crude oil. Cohesity Gaia fulfills this promise by translating vast data lakes into meaningful insights, enhancing operational efficiency, and unleashing the full potential of an organization’s data assets.

Statton accentuated how Cohesity Gaia expedites informed decision-making by enhancing data accessibility and comprehensibility within businesses.

Prioritizing Security and Privacy

One persistent concern with generative AI involves the accuracy and validity of the underlying training data, particularly in these early stages. Effective communication hinges on the trustworthiness of the responses generated.

Sam Curry, VP, and CISO at Zscaler, discussed the challenges associated with utilizing large generative AI models like ChatGPT, emphasizing the importance of the quality of information available to the model. Ensuring data accuracy and protection is paramount, especially in environments with varying access levels and permissions.

Statton highlighted the option for customers to merge clean backup data with on-demand context retrieval, emphasizing the importance of maintaining stringent data access controls and adhering to zero-trust security principles.

Democratizing Enterprise Data

Statton demonstrated the functionality of Cohesity Gaia through a video, showcasing how the platform democratizes data access and empowers a diverse range of users to leverage the organization’s data effectively. By fostering a culture of data-driven decision-making through conversational interactions, Cohesity Gaia caters not only to IT professionals but also to compliance officers, researchers, and other stakeholders.

Establishing a New Benchmark for Data Management and AI Integration

Platforms like Cohesity Gaia herald a future where data management is not only streamlined and secure but also aligned with human thinking and communication patterns. Rapid data-to-insights conversion is essential in navigating the complexities of the modern business landscape. Cohesity Gaia stands out as a robust solution for organizations seeking to maximize their data assets intelligently, securely, and efficiently.

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Tags: Last modified: March 8, 2024
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