Vasu Murthy is the SVP and Chief Product Officer at Cohesity, bringing over 25 years of enterprise software experience across data security, protection, and analytics. Prior to joining Cohesity, he held leadership roles at Rubrik, Oracle, and DataScaler, contributing to product growth and large-scale innovation.
Cohesity is the leader in AI-powered data security. Over 13,600 enterprise customers, including over 85 of the Fortune 100 and nearly 70% of the Global 500, rely on Cohesity to strengthen their resilience while providing Gen AI insights into their vast amounts of data. Formed from the combination of Cohesity with Veritas’ enterprise data protection business, the company’s solutions secure and protect data on-premises, in the cloud, and at the edge
You co-founded DataScaler, which was later acquired by Oracle. What lessons from your startup journey still guide your decision-making today?
Finding product market fit was our primary goal in the early stages at DataScaler. While we had many enthusiastic prospects for the product, enthusiasm did not always translate into a repeatable use case. The power is in asking the right questions. If all you ask is “What would you like?” or “Would you use this?”, people are often in the mindset of their ideal self, thinking about what they’d like to use or need in a perfect world, and it doesn’t always reflect what they need in their day-to-day reality.
If something is truly important to a customer, chances are they’re already doing it, likely not efficiently or enjoyably. They might be using a clunky product they don’t like, spending more money, or handling things manually and wishing they could get time back. The better questions to ask are: “What are you doing today that’s hard?” or “What would save you time or money?” When you start with the right questions, you uncover problems that are worth solving.
What drove your decision to move from a giant like Oracle into the fast-paced world of Rubrik and later Cohesity?
I think of my career as a series of missions. Reid Hoffman calls it “Transformational Tours” in his book, The Alliance. A typical mission for me lasts 2-3 years and ends with a specific outcome for the business, and then it’s time to work on something new. While I was at Oracle, I was given a project that became a three-year mission. Once completed, I asked, “What’s next?” and they said, “Something even bigger!”, so I assembled a team and began the next mission. That cycle repeated itself, and each time, the challenge grew.
At the end of my third mission at Oracle, I was craving something at the pace and perspective of a high-growth startup, which led me to Rubrik. After Rubrik’s IPO, I took some time off to think about what was next, and set out to join a team with an exciting challenge, which is how I came into my role at Cohesity.
What unique opportunities did you see at Cohesity that convinced you this was the right next chapter in your career?
Cohesity’s recent acquisition of Veritas’ enterprise data protection business is exactly the kind of project that I was looking for. The opportunity to play a key role in integrating the companies while charting a smooth transition for the large customer base is both challenging and rewarding. I’m privileged to contribute to shaping the culture, influence product development, and making this transformation successful for our employees and customers.
You joined Cohesity just before the Veritas acquisition. What was your first focus as CPO coming into this high-stakes moment?
For a CPO, understanding the mindset of customers and employees is just as important as understanding the product and the market. Our customers are global, and our people have been through different experiences. Getting a message across that resonates with all of them is crucial.
Beyond communication, my top priority is to increase the pace of innovation we deliver to our customers, and earn the right to continue to expand our footprint. There’s an opportunity to guide our customers to the future of data security and AI.
Cohesity has a strong AI-first vision. How are you thinking about AI as a product layer versus an embedded capability?
Cohesity leverages AI in all aspects — from detecting anomalies and classifying data to helping customers accelerate and strengthen cyber recovery. With hundreds of exabytes of data under our management, there’s a big opportunity to unlock AI-driven insights from all across the platform.
Cohesity was built from the ground up as a platform, which makes us unique in this market. Designed to support multiple applications from the start, Cohesity has a strong position in many use cases on data. Customers pay us to bring their data into our platform, which gives us a powerful opportunity to build and deliver applications on top of it.
How do tools like Cohesity Gaia redefine how enterprises interact with their data?
80% of enterprise data is unstructured and traditionally difficult to manage or analyze, and generative AI has provided opportunities to extract insights and value from it.
To leverage unstructured data, it needs to be gathered from a variety of sources, cleaned to ensure it does not have unwanted private, sensitive data, and provided in immutable views for RAG and other ways to derive insights. Even when data is available, it takes significant effort to build the AI infrastructure to deliver insights.
Cohesity Data Platform already gathers and secures data from all locations, and we also built Gaia, a full-fledged RAG application to derive insights from data. This allows users to interact with their data using natural language, generate valuable insights, and seamlessly unify company knowledge across various data types and locations.
What are the most exciting customer use cases you’ve seen so far for AI-powered conversational search and threat detection?
There’s so much data worldwide that many customers don’t even know what they have. Being able to unlock that and leverage for more information is very powerful for business. One aspect I find particularly interesting is the concept of data sovereignty. In today’s geopolitical climate, countries are increasingly concerned about whether data stored within their borders gives their citizens control. A key question that’s been coming up, especially with AI, is whether these AI services are hosted in the cloud. People are worried about whether they can query their data and who can access it.
Cohesity stands out to me in situations like this because it offers a solution through enabling on-premises data management. With Cohesity, customers don’t need to move their data to the cloud or worry about entities managing it in other countries. The growing concern around data sovereignty and “data gravity” means that more organizations want to keep things on-premises, and we can provide exactly that solution, working with our hardware partners and NVIDIA.
How do you ensure alignment across product, design, and documentation—especially when launching AI-first experiences?
Success of a company depends on all functions operating in harmony – not just product, design and documentation. Ideas can come from anywhere and when people feel heard, they feel a sense of ownership that drives the best outcome.
It is important to include all stakeholders early on, listen to them, and ensure they all have a say in the outcome. Product teams need to be good idea curators and help prioritize, designers need to keep customer experience at the forefront, and documentation teams need to focus on minimizing the time spent in documents by working with designers, providing in-line guidance as necessary. AI has a huge role to play in developing and delivering this experience.
What frameworks help you prioritize between customer pain points, visionary innovation, and technical debt?
It pays to start from first principles when determining priorities and shaping our approach. Frameworks can be helpful for communicating this, especially when they’re well-aligned. That said, I believe most products can generally be categorized into three types.
First, there are new products with few customers, where innovation should be the main focus. Then, you have the core products that are the bread and butter. Innovation is important here, but addressing customer pain points should also be a priority. Lastly, you have long-term, mature products that are well-established. In this case, the focus shifts more to managing customer pain points and technical debt.
What are your goals for Cohesity’s product portfolio over the next 12 to 18 months?
We’ve found so much that fits between Cohesity and Vertias’ enterprise data protection business since the acquisition. It’s the fastest I’ve ever seen two product suites come together. In Veritas’ most recent iteration, they converted their backup solution into a set of microservices within containers. Conversely, Cohesity started as a container-based application platform built on a flexible data layer. Because of this, it’s possible to drop Veritas services onto the Cohesity platform, and things work seamlessly because the data platform works with both.
Over the next 12 to 18 months, we want our workload support, data security and AI services to be common for all our customers. We’re also building a seamless upgrade path for all customers to get to a future proof platform for their data.
A product that I’m particularly excited about is RecoveryAgent, Cohesity’s new Agentic AI cyber orchestration solution. The first new offering from the joint development efforts of Cohesity and Veritas, it provides customers with easy cyber recovery preparation, testing, and automation to strengthen security postures, increase confidence in incident response, and prove compliance.
What advice would you give to other CPOs navigating this AI-dominated landscape?
People are feeling the immediate need to incorporate AI into applications. Often this is in the form of making workflows easier and assisting people in being more productive. While this is useful for customers, it is unlikely that customers pay significantly more for this incremental productivity improvement.
True AI differentiation requires re-thinking the workflows completely driven by AI. The technology is evolving rapidly and will become more valuable as the AI accuracy improves. AI can be great for natural language interactions and some planning, the core logic still requires a lot of validation, monitoring, error-correction, and scaffolding. While AI driven apps will improve over time, there is money to be made in AI and data infrastructure.
Thank you for the great interview, readers who wish to learn more should visit Cohesity.
