Cohesity recently introduced its new Gaia capability, bringing AI-powered enterprise search to its data backup environments.
This is not an obligatory AI-washing announcement, as many vendors feel they must keep making these days. In contrast, Gaia uses AI to maximize the return on your secondary data assets.
In 2019, TechTarget’s Enterprise Strategy Group introduced a maturity model that predicted the evolution of the traditional backup market into the data intelligence market, including the use of automation and AI/ML. In the model, we identified that the requirement for context and content about the data is becoming more acute as new regulations and the need for data to support digital transformation change the role of data in the enterprise. People, processes, and workflows must use data more intelligently. It’s really about business outcomes and the notion of data as a true asset that can be leveraged to create a return on investment or avoid costs and risks. Our model identified the critical role of AI/ML in reaching data management nirvana.
That’s what Gaia delivers in many ways, but there is more than meets the eye.
Why? It uses retrieval-augmented generation (RAG) to give end users conversational and context-rich responses to gain insights from their secondary enterprise data.
Cohesity’s new tool combines a conversational interface, AI-powered search—on indexed enterprise secondary data—and LLM response. It is designed to help organizations improve their decision-making speed and accuracy while securely searching enterprise data in a compliant fashion. Key features include natural language queries, role-based access, RAG capabilities, and a SaaS-based platform.
The use case Cohesity is putting forward relates to investigative compliance research, such as detecting violations of personally identifiable information exposures—in other words, searching data from your backups for compliance issues. It is easy to imagine adding outside data to identify the penalties or other requirements associated with this internal data. The key is that this happens securely as “your” data is never exposed externally but can be augmented by or augment external data.
Our initial view, with the caveat that our research firm has not functionally or technically validated the solution, is that Gaia is a timely platform that extends Cohesity’s capabilities, making it faster, more automated, and more efficient. Its AI assistant prioritizes privacy, risk mitigation, data protection, and security.
It is designed to change end users’ ability to unlock value in their company’s data assets without a Ph.D. in data science.
We see the platform’s user-friendly interface and expandable ecosystem as critical to allow for external data integration and complex tasks to be performed with ease. It’s an ideal solution for enterprises seeking to maintain regulatory compliance, and its simple question-and-answer feature makes it an efficient tool for additional business and technical processes in time.
While it might be a little early to say with Gaia, one of the significant benefits of using generative AI for conversational search on enterprise data is its ability to deliver a personalized experience. Every person accessing the data will ask different questions, and it’s impossible to predict them all. For instance, someone could ask about compliance while another group asks about security. The variety of questions presents an exciting opportunity for Cohesity to provide a comprehensive, context-rich and tailored solution to its users.
Beyond the compliance use case, we expect Cohesity to deliver what we call “generative data protection” capabilities through Gaia, focusing on cyber resilience and cyber recovery. These are inherently more complex than simply discovering data misuse or ineffective data governance policies, but they are also well-known territory for Cohesity’s platform.
Also, we appreciated how Cohesity showed some transparency in the pricing model, and organizations will need guidance based on what they expect from their user base. There will likely be a gradual process as they navigate this, with limitations based on the number of answers and the amount of storage indexed. Monitoring this pricing model is crucial, as it may set the stage for the entire market.
We believe that Cohesity has an excellent opportunity to establish itself as a leader in the market with this announcement, as it is capacity- and answer-based. Over time, the number of answers and capacity will likely determine the subscription price or pricing structure.
While it might seem like the result of years of work in intelligent data management of non-production/backup data for Cohesity, it’s just the beginning of the next phase of their technological evolution. This new phase involves integrating technologies with a broad ecosystem of cyber and AI partners and the elephant in the room: Veritas. This will happen when the acquisition deal closes in the next few quarters. With this in mind, Cohesity must execute on all fronts to ensure the continued success of Gaia and the future “new” Cohesity.
Competitors are constantly working on their AI-focused initiatives, so Cohesity cannot afford to stand still. The year 2024 is sure to be an exciting year for the company and the market at large.
Enterprise Strategy Group is a division of TechTarget. Its analysts have business relationships with technology vendors.
