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, depend on Cohesity to strengthen their resilience while providing Gen AI insights into their vast amounts of knowledge. Formed from the mix of Cohesity with Veritas’ enterprise data protection business, the corporate’s solutions secure and protect data on-premises, within the cloud, and at the sting
You co-founded DataScaler, which was later acquired by Oracle. What lessons out of your startup journey still guide your decision-making today?
Finding product market fit was our primary goal within the early stages at DataScaler. While we had many enthusiastic prospects for the product, enthusiasm didn’t at all times translate right into a repeatable use case. The facility is in asking the appropriate questions. If all you ask is “What would you want?” or “Would you utilize this?”, persons are often within the mindset of their ideal self, fascinated with what they’d wish to use or need in an ideal world, and it doesn’t at all times reflect what they need of their day-to-day reality.
If something is actually essential to a customer, likelihood is they’re already doing it, likely not efficiently or enjoyably. They could be using a clunky product they don’t like, spending more cash, or handling things manually and wishing they might get time back. The higher inquiries to ask are: “What are you doing today that’s hard?” or “What would prevent time or money?” While you start with the appropriate questions, you uncover problems which might be value solving.
What drove your decision to maneuver from an enormous like Oracle into the fast-paced world of Rubrik and later Cohesity?
I believe of my profession 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 selected consequence for the business, after which it’s time to work on something recent. While I used to be at Oracle, I used to be given a project that became a three-year mission. Once accomplished, I asked, “What’s next?” they usually said, “Something even greater!”, so I assembled a team and commenced the subsequent mission. That cycle repeated itself, and every time, the challenge grew.
At the top of my third mission at Oracle, I used to be craving something on the pace and perspective of a high-growth startup, which led me to Rubrik. After Rubrik’s IPO, I took some day without work to take into consideration what was next, and set out to hitch a team with an exciting challenge, which is how I got here into my role at Cohesity.
What unique opportunities did you see at Cohesity that convinced you this was the appropriate next chapter in your profession?
Cohesity’s recent acquisition of Veritas’ enterprise data protection business is strictly the sort of project that I used to be searching for. The chance to play a key role in integrating the businesses while charting a smooth transition for the big customer base is each difficult 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 shoppers and employees is just as essential 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 extend the pace of innovation we deliver to our customers, and earn the appropriate to proceed to expand our footprint. There’s a possibility to guide our customers to the long run of knowledge security and AI.
Cohesity has a robust AI-first vision. How are you fascinated with AI as a product layer versus an embedded capability?
Cohesity leverages AI in all points — from detecting anomalies and classifying data to helping customers speed up and strengthen cyber recovery. With a whole lot of exabytes of knowledge under our management, there’s a giant opportunity to unlock AI-driven insights from all across the platform.
Cohesity was built from the bottom up as a platform, which makes us unique on this market. Designed to support multiple applications from the beginning, Cohesity has a robust position in lots of use cases on data. Customers pay us to bring their data into our platform, which supplies us a strong opportunity to construct 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 administer or analyze, and generative AI has provided opportunities to extract insights and value from it.
To leverage unstructured data, it must be gathered from quite a lot of sources, cleaned to make sure it doesn’t have unwanted private, sensitive data, and provided in immutable views for RAG and other ways to derive insights. Even when data is on the market, it takes significant effort to construct 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 enables users to interact with their data using natural language, generate worthwhile insights, and seamlessly unify company knowledge across various data types and locations.
What are probably the most exciting customer use cases you have seen to this point for AI-powered conversational search and threat detection?
There’s a lot data worldwide that many shoppers don’t even know what they’ve. Having the ability to unlock that and leverage for more information could be very powerful for business. One aspect I find particularly interesting is the concept of knowledge sovereignty. In today’s geopolitical climate, countries are increasingly concerned about whether data stored inside their borders gives their residents control. A key query that is been coming up, especially with AI, is whether or not these AI services are hosted within the cloud. Individuals are frightened about whether or not they can query their data and who can access it.
Cohesity stands out to me in situations like this since it offers an answer through enabling on-premises data management. With Cohesity, customers need not move their data to the cloud or worry about entities managing it in other countries. The growing concern around data sovereignty and “data gravity” signifies that more organizations wish to keep things on-premises, and we will 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 an organization is determined by all functions operating in harmony – not only product, design and documentation. Ideas can come from anywhere and when people feel heard, they feel a way of ownership that drives the very best consequence.
It will be significant to incorporate all stakeholders early on, hearken to them, and ensure all of them have a say within the consequence. Product teams must be good idea curators and help prioritize, designers must keep customer experience on the forefront, and documentation teams must concentrate on minimizing the time spent in documents by working with designers, providing in-line guidance as obligatory. AI has an enormous role to play in developing and delivering this experience.
What frameworks enable you prioritize between customer pain points, visionary innovation, and technical debt?
It pays to start out from first principles when determining priorities and shaping our approach. Frameworks may be helpful for communicating this, especially once they’re well-aligned. That said, I consider most products can generally be categorized into three types.
First, there are recent products with few customers, where innovation ought to be the principal focus. Then, you might have the core products which might be the bread and butter. Innovation is essential here, but addressing customer pain points also needs to be a priority. Lastly, you might have long-term, mature products which might be well-established. On this case, the main target shifts more to managing customer pain points and technical debt.
What are your goals for Cohesity’s product portfolio over the subsequent 12 to 18 months?
We have found a lot that matches between Cohesity and Vertias’ enterprise data protection business for the reason that acquisition. It is the fastest I’ve ever seen two product suites come together. In Veritas’ most up-to-date iteration, they converted their backup solution right into a set of microservices inside containers. Conversely, Cohesity began as a container-based application platform built on a versatile data layer. For this reason, it’s possible to drop Veritas services onto the Cohesity platform, and things work seamlessly because the info platform works with each.
Over the subsequent 12 to 18 months, we wish our workload support, data security and AI services to be common for all our customers. We’re also constructing a seamless upgrade path for all customers to get to a future proof platform for his or her data.
A product that I’m particularly enthusiastic about is RecoveryAgent, Cohesity’s recent Agentic AI cyber orchestration solution. The primary recent 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?
Individuals are feeling the immediate need to include AI into applications. Often that is in the shape of constructing workflows easier and assisting people in being more productive. While this is beneficial for patrons, it’s 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 can turn out to be more worthwhile because the AI accuracy improves. AI may be great for natural language interactions and a few planning, the core logic still requires loads of validation, monitoring, error-correction, and scaffolding. While AI driven apps will improve over time, there’s money to be made in AI and data infrastructure.
