What are the different types of AI?

Generative AI uses algorithms to generate new content (written content, images, video, audio, and computer code, etc.) based on user input. Unlike earlier versions of AI, generative AI can create new content, like news articles, poetry, or cyber threat analyses, presented in a conversational UI. Conversational AI mimics human conversation and speech using techniques such as NLP and transformers to generate personalized responses. Cognitive AI uses techniques such as natural language processing (NLP) and machine learning (ML) to mimic human cognitive abilities. Retrieval AI searches information from large datasets, and uses AI techniques to retrieve the most relevant results matching the intent of the user’s query.

How is AI used for data management?

AI can enhance data management and make it more efficient, such as by automating data classification or detecting anomalies. Cohesity built AI into several of our products to help detect threats, classify large volumes of unstructured data, and protect critical data and workflows. Two ways we use AI include: We use AI to boost data security. We can secure data and strengthen your cyber resilience with threat detection and data classification. We help you get more from your stored data. Cohesity Gaia is an AI-powered data insights solution that can conduct semantic searches and create answer summaries from your enterprise data. Using your backups as a data source, Cohesity Gaia can unlock the knowledge in your data.

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Responsible AI

Define what data should be shared with your AI models and protect access to it with RBAC controls. Promote responsible AI, transparency, and accountability around access and policies.

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Overview

Maximize your potential, minimize your risk

The promise of AI technologies means change for the enterprise. While these advancements bring us into a new era of possibility, they can also come at a cost. So we offer both commitments and safeguards for responsible AI use.

Transparency

Protect access to data with role-based access controls. Promote transparency and accountability around access and policies.

Governance

Help ensure the security and privacy of data used by AI models and the workforce—so the right data is exposed only to the right people with the right privileges.

Access

Access data responsibly via RBAC, non-destructively index the data, then search it and summarize it with speed and efficiency.

Demo: Usher in a new era in data security and management with AI

Watch as Gregory Statton, Office of the CTO - Data & AI, talks about Cohesity's vision for AI, including helping customers reduce their time to action through Operational Insights. He also shows the advancements in search and discovery using retrieval augmented generation (RAG) to drive rich conversations with data.

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Video thumbnail of demo with Greg Statton

Benefits

Retrieval augmented generation (RAG) AI in action

Start having a conversation with your data. Using common language, ask questions about your data and await responses. Ask follow-up questions, dig deeper into datasets, and let Cohesity Gaia support more in-depth data analysis.

Conversational data

Use natural language to create queries that can unlock deep learnings and insights hidden in your data.

AI-powered search

Advanced search capabilities, powered by RAG AI technology, can deliver informed answers to questions hidden in your business and application data.

Turning data into knowledge

Gain deep, meaningful insights and learnings into your organization and data.

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Conversational search providing insights with Cohesity

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Using AI to unlock insights from enterprise data

See our shared vision for how customers of Microsoft and Cohesity can securely use AI to transform data security initiatives.

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Testimonials

Transformation for me means simplicity and speed. With Cohesity, everything is easier across the board—whether in performance, security, or reporting. Cohesity’s strong collaboration with partners such as Nvidia will open new opportunities in the future for greater insight and value from our data."

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Martin Hofmann

Head of Information Technology, Infra Fürth

With data in multiple countries, locations and subsidiaries, AI capabilities from Cohesity will help unlock data from the current silos to provide business insights and accelerate knowledge at JSR. Cohesity Gaia will help enable our employees to search across all our enterprise data, whether in files, SharePoint, or OneDrive to foster greater innovation for our business.”

Ryan Reed

Head of IT Products and Services, JSR Corporation

Cohesity is helping customers get more insights from data by integrating Cohesity’s AI-ready, heavily indexed, fully-hydrated, cached, and easily-searchable data structure with Azure OpenAI.”

Patrick Moorhead

Founder, CEO and Chief Analyst, Moor Insights & Strategy

Vertex AI is one of the best platforms for building, deploying, managing and scaling ML models–and we’re excited that Cohesity is joining our growing open ecosystem to help more customers get value from their data via AI. Cohesity’s excellent data security and management capabilities, combined with Google Cloud’s powerful generative AI and analytics capabilities, will help customers get exceptional insights into their backup and archived data.”

Thomas Kurian

CEO, Google Cloud

More AI use cases for the enterprise

Sanjay Poonen and Manuvir Das discuss an enterprise AI stack in every cloud.

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How Microsoft LLMs can be used in Cohesity applications

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Learn more about responsible AI and data governance

Responsible AI is an approach to developing and deploying artificial intelligence (AI) from both an ethical and legal point of view. The goal of responsible AI is to employ AI in a safe, trustworthy, and ethical fashion.

Generative AI uses algorithms to generate new content (written content, images, video, audio, and computer code, etc.) based on user input. Unlike earlier versions of AI, generative AI can create new content, like news articles, poetry, or cyber threat analyses, presented in a conversational UI.
Conversational AI mimics human conversation and speech using techniques such as NLP and transformers to generate personalized responses.
Cognitive AI uses techniques such as natural language processing (NLP) and machine learning (ML) to mimic human cognitive abilities.
Retrieval AI searches information from large datasets, and uses AI techniques to retrieve the most relevant results matching the intent of the user’s query.

AI can enhance data management and make it more efficient, such as by automating data classification or detecting anomalies.

Cohesity built AI into several of our products to help detect threats, classify large volumes of unstructured data, and protect critical data and workflows.

Two ways we use AI include:

We use AI to boost data security. We can secure data and strengthen your cyber resilience with threat detection and data classification.
We help you get more from your stored data. Cohesity Gaia is an AI-powered data insights solution that can conduct semantic searches and create answer summaries from your enterprise data. Using your backups as a data source, Cohesity Gaia can unlock the knowledge in your data.