Rahul Ponnala is the co-founder and CEO of Granica — the world’s first AI efficiency platform — which is on a mission to make AI affordable, accessible and safe to use.
He previously served as Director of Storage and Integrations at Pure Storage, where he engineered and integrated large-scale databases and file storage systems powered by all-flash technology. As a governing board member of The FinOps Foundation under The Linux Foundation, he helps shape the future of cloud financial management. A multidisciplinary academic, Rahul’s research spans mathematics, information theory, machine learning and distributed systems. He holds a portfolio of patents in computational statistics and data compression.
M.R. Rangaswami: What are the hard business and/or technology problems that inspired you to found Granica?
Rahul Ponnala: Advancements in deep learning have been powered by ever-larger models processing ever-growing amounts of data. The performance output of an AI algorithm is primarily determined by the diversity and volume of data it can access. So, as AI becomes integral to products and services in nearly every domain, access to “high quality” data will become both a critical necessity and a fundamental constraint, ultimately dictating the pace and effectiveness of AI investments at enterprises.
To derive “high quality” data, enterprises must extract the maximum amount of information from their data stores and thereby maximize the value of their data – but the challenge here is two-fold. As data volume grows, so do the costs of managing, processing and storing it in the cloud.
Second, as the potential for insight from new data sources increases, the risk of misuse and mishandling increases. Enterprises who can successfully contain rising cloud costs associated with growing data stores, while ensuring the safe use of data in AI to preserve its analytical value, will develop formidable, competitive moats.
Since its inception, Granica has been developing cutting-edge and efficient solutions to allow enterprises to maximize the value of their data – our AI efficiency services are no exception. We are witnessing a Cambrian-like explosion in the pace of deployment of AI into various apps, products and services, marking a major technological shift in the future of computing. And while there has been meaningful progress on the computing infrastructure and algorithmic layers of AI and ML, there has been little progress in increasing the signal-to-noise ratio of the data fueling these algorithms.
This is a very difficult problem, involving deep information and computer science developments, combined with large-scale systems engineering – and this is precisely the problem Granica is focused on solving.
M.R.: How will your AI efficiency platform impact the future of enterprise AI/ML adoption? What is your advice to organizations that want to adopt a more efficient and productive cloud data architecture for their AI initiatives?
Rahul: Extracting the maximum amount of information from data stores is perhaps the most critical
element in the long-term success (or lack thereof) of an organization’s AI investments and strategy. So by delivering a platform capable of helping organizations do just that, Granica is democratizing access to AI by directly making AI more affordable, more accessible and safe to use.
By now, most organizations have grasped the importance and criticality of integrating an AI strategy into their corporate planning-and in fact, this was the most popular question Wall Street analysts asked the management teams of big tech companies this past earnings cycle.
Yet, most organizations – large and small – are left hamstrung in determining where to start and how to do so in an efficient manner, while operating under a set of both economic and time constraints imposed by the market.
When speaking with customers about AI, the number one question that comes up is: “How can I get started and where should I get started?” And our answer, non-surprisingly, is: “Let’s first evaluate the effectiveness and efficiency of your organization’s data strategy.”
By getting plugged into a customer’s environment and providing deep, informative analytics with respect to their cloud data stores and how their data is being used, we are able to provide direct visibility and insight into the inefficiencies present in that customer’s data architecture and gain a deep understanding of that customer’s data and workload characteristics.
This then allows Granica to quickly configure and tailor our platform to their environment and thus accelerate the time to value for the customer. By providing customers with efficient building blocks and tools for their data architecture and AI-powered applications, we can help them optimize their data access, storage and compute resources and thus maximize the value of their data.
M.R.: You’ve expressed that people are integral to your company. What are your values/philosophies as a leader with respect to growing successful teams?
This not only allows us to bring our best professional selves to the office but also build long-term friendships and trust with one another. We want each of our employees to feel comfortable turning to one another to seek guidance, help and coaching – not just about “work”, but also about personal circumstances.
At Granica, our employees, or “ninja warriors” as we like to call them, are the backbone of our organization. We share successes as a team, we make mistakes as a team and we challenge each other.
By doing so, we leverage the collective intelligence of the whole to put everything we can into delivering exceptional experiences for our customers and inspiring one another along the way.
Everyone at Granica lives by the motto of “Whatever it Takes” and we actually have this signage up on our wall in the lobby of our headquarters. It doesn’t matter whether you’re an individual contributor or manager at Granica – we want everyone to be leaders and we want to provide the resources, mentorship and growth opportunities to allow each ninja to grow their careers to new heights.
M.R. Rangaswami is the Co-Founder of Sandhill.com