Granica is the world’s first AI efficiency platform and it boosts ROI on AI by increasing the information efficiency of AI training data, freeing up resources that C-level executives and enterprise AI teams can use to reduce costs and improve AI performance and outcomes. Pulse 2.0 interviewed Granica co-founder and CEO Rahul Ponnala to learn more about the company.
Rahul Ponnala’s Background
Before founding Granica, Ponnala served as Director of Storage and Integrations at Pure Storage. And Ponnala said:
“In this role, I helped engineer and integrate large-scale databases and storage systems powered by all-flash technology and build robust interfaces to bridge on-premises systems with distributed clouds. I’m a multidisciplinary academic with research that spans mathematics, information theory, machine learning, and distributed systems. From this research, I hold a portfolio of patents in computational statistics and data compression. And finally, as an angel investor, I support emerging tech startups pushing boundaries in AI, robotics, and medicine.”
Formation Of Granica
How did the idea for Granica come together? Ponnala shared:
“Looking ahead, it’s clear that AI will become integral to products and services in every domain, irrespective of company size. Enterprises today can leverage a variety of base models available through open-source platforms and utilize the computational infrastructure offered by their preferred cloud providers, but these ingredients are not fundamental constraints. We realized that information-rich data would be that fundamental constraint and thus dictate the pace and direction of AI developments.”
“As AI proliferates and models are commoditized, proprietary data becomes a gold mine. The ability to build specific models using unique data sets within secure boundaries helps establish formidable competitive moats. Extracting the maximum information from data widens and deepens this moat. However, this golden opportunity comes with its own set of challenges.”
“First, cost. As data volume grows, so does the cost of managing, processing, and storing it—particularly in the cloud. Enterprises must contain these costs without compromising the value of data. Simple deletion or archiving isn’t a sustainable long-term strategy.”
“Next, privacy risks. With the power of data comes the responsibility of safeguarding it. As the potential for insight from data increases, so does the potential for misuse. Rising public awareness about data privacy has led to stringent legislation, such as the EU’s General Data Protection Regulation (GDPR). Businesses must ensure the safe use of data in AI and analytics while preserving its analytical value. This requires innovative ways to detect and anonymize data without sacrificing its core value.”
“By effectively addressing these challenges, businesses can reduce costs, protect privacy, and increase the information density within their data sets. Information density is the amount of meaningful information that can be extracted from a given data set. Higher information density leads to simpler, more accurate, and more insightful models. By optimizing the information density of their proprietary data, companies can unlock the full potential of AI and gain a significant competitive advantage.”
“We recognized that overcoming these challenges and achieving higher information density for AI applications requires a transformation in traditional AI architectures. This transformation takes the form of an entirely new, seamlessly integrated layer in the stack – a layer that effortlessly blends with customers’ existing cloud-native infrastructure, ensuring that their data stays secure while providing easy accessibility through an API.”
“And that’s exactly what we founded Granica to do.”
Favorite Memory
What has been Ponnala’s favorite memory working for Granica so far? Ponnala reflected:
“It is much too hard to think of a single favorite memory since the founding of Granica. That said, I think my favorite thing has been observing the growth in our team and how far we’ve come since the early days.”
“At the start of 2019, Tarang Vaish (co-founder and CTO) and I were working out of our investor’s offices in Palo Alto. Then, in 2020, we upgraded to a small office which was just a couple hundred square feet in Mountain View. During this time, we recruited some critical engineers and our headcount grew to about 12 people. In the Fall of 2021, we moved into our – now current – headquarters in downtown Mountain View, where over 30 of our ninjas come to work each day.”
“One of my favorite things about the office is sitting at the lunch tables each day: everyone in the office congregates to have some yummy food, share laughs, and participate in stimulating conversation with one another. It is really an amazing opportunity to get to know one another on a much deeper personal level and foster true friendships.”
“Another favorite of mine is taking a walk through the office and seeing the rush of activity taking place at any moment: the whiteboarding conversations, the coffee chats, the customer meetings in conference rooms, the energy and enthusiasm behind these interactions is palpable. And for me, this is something I derive a tremendous amount of inspiration from.”
Challenges Faced
What are some of the challenges Ponnala faced in building the company, and has the current macroeconomic climate affected the company? Ponnala acknowledged:
“We have a big vision and deep roadmap of AI efficiency services with lots of complex engineering and mathematical problems to be solved. At Granica, our employees are the backbone of our success. Hiring top talent while the company was operating in stealth was no easy task, and we are proud of the incredible team we have built thus far. Now that we have exited stealth, we can speak more freely to prospective candidates about what we’re doing and why. Nonetheless, successfully executing on our future roadmap hinges on our ability to retain and attract world-class engineers and researchers.”
“As an early-stage vendor, selling into enterprises and the Fortune 1000s of the world is always an uphill battle and you must convince executives at the top to move away from existing tools and adopt novel solutions. But, we’ve performed remarkably well in this regard and actually developed critical relationships with most of our existing customers while we were still in stealth, which says a lot about our platform. In a post-stealth world, our reputation with our customers is growing favorably, and we expect that C-suite selling at these enterprises will be a critical growth lever for us in the future.”
“With respect to the macroeconomy, Granica’s business operations have not been impacted really. For one, we have a strong balance sheet capable of funding our growth initiatives. Second, while the average sales cycle has elongated for traditional B2B vendors, the demand for our cost-saving services has dramatically increased. So, the current macro climate has actually served as a catalyst for Granica in many ways.”
Core Products
“We provide a suite of cutting-edge efficiency services accessible through a single platform API. Operating within our customers’ cloud environment, we ensure their data never leaves their secure boundary. We provide rich, granular insight into how data is stored and accessed, and it’s designed to scale autonomously – from zero to any volume – eliminating the need for any tuning. Here’s how our three initial services work:
Granica Crunch: A game-changer for enterprise AI, this service losslessly reduces the size of data either in the background or in motion. It applies novel compression and deduplication algorithms to petabyte-scale data of various modalities. The result? Up to an 80% reduction in data size, leading to lower costs for storing and transferring objects in Amazon S3 and Google Cloud Storage. This reduction could translate into significant cost savings, potentially amounting to thousands or even millions of dollars annually, depending on data volumes. Additionally, it cuts down API costs associated with accessing this data by up to 90%, offering even more opportunities for substantial savings.
Granica Screen: This data privacy service is tailored for enterprise AI. It uses byte-precise algorithms to detect and safeguard Personally Identifiable Information (PII) and other sensitive data with precision and recall rates exceeding 99% for our customers. This level of accuracy significantly reduces the risk of data breaches, potentially saving organizations from the steep fines associated with non-compliance and the reputational damage that can result from mishandling sensitive data. Moreover, by unlocking sensitive data for safe AI and analytics use, Granica Screen allows organizations to harness more of their data’s potential.
Granica Chronicle: This is a GenAI-powered SaaS offering that provides deep visibility and analytics into how data is stored and accessed in cloud object stores. Chronicle provides an AI-powered, natural language interface that makes exploration, visualization, and collaboration incredibly simple. After entering in simple prompts, users are presented with relevant visualizations in graphs and tables that answer key questions related to data security and compliance, cost optimization, and chargeback enablement. Chronicle is also collaborative, enabling users to participate in a shared view of prompt-based results and history with other cross-functional Chronicle users across their organization. All without any knowledge of SQL and/or dashboard creation from any user.
Granica Crunch is generally available now, and Granica Screen and Granica Chronicle are available via early access preview. All three work together to provide a comprehensive solution, increasing information density, reducing cost, and preserving privacy—driving AI Efficiency forward.
Finally, our revolutionary business model allows our customers to pay only for the tangible outcomes we deliver for them, upending the traditional consumption-based business models. We believe this is the way forward.”
Evolution Of Granica’s Technology
How has Granica’s technology evolved since launching? Ponnala noted:
“Our technology evolution since our founding in 2019 tracks in two primary dimensions: service scope and platform scale. We started out with Granica Crunch, our data reduction API, and we’ve been rapidly increasing the scope of supported data types (e.g., LiDAR, parquet, TIFF, PNG etc.) as well as the degree of data reduction for those data types in order to increase the savings our customers realize from using Crunch.”
“From there, we’ve expanded scope with Granica Screen, a data privacy service complementary to Crunch, and Granica Chronicle, a GenAI SaaS service for improving security, compliance, and application cost-effectiveness, both currently in early access preview. We have a deep roadmap of other efficiency services and will continue to evolve and increase our service scope in order to make AI safer to use, more effective, and more affordable.
“Our platform supports all our API services, current and future, and so here the evolution is around ever-increasing scale and ease of customer onboarding and consumption. In the early days, our platform operated at terabyte scale. Today, we easily handle tens of petabytes, and we’re on a path to exabyte-scale.”
Significant Milestones
What have been some of Granica’s most significant milestones? Ponnala highlighted:
“We deeply obsess over delivering measurable value to our customers, and so we treat each and every new deployment as a critical milestone. That said, some noteworthy internal milestones include our Series A funding round led by Pete Sonsini and Vanessa Larco at New Enterprise Associates (NEA); opening up our physical headquarters in Mountain View, and of course, our launch out of stealth into the public domain with coverage in the Wall Street Journal.”
Customer Success Stories
Upon asking Ponnala about customer success stories, he cited:
“HERE Technologies is the world’s #1 location services provider, enabling customers to navigate a data-rich world with a complete, accurate and easy-to-use digital representation of the physical world. They embarked on a multi-million dollar savings initiative with us, reducing their at-rest cloud storage costs by 47% without archival or deletion. This is what Jason Fuller, Head of Cloud and Employee Foundations at HERE, has to say: ‘As the leading location technology platform, we are a data-intensive business that heavily utilizes AI. Granica can handle our petabyte-scale demands. The efficiencies we’ve experienced since deploying Granica has allowed us to reallocate investments back into our business.’”
“Nylas is a communications platform that offers customers API solutions to quickly and securely build email, scheduling and work automation features into their applications. With our AI Efficiency Platform, Nylas cut their cloud storage API costs by 90% and delivered a faster, more responsive end-user experience all without re-architecting their applications. This is what John Jung, VP of Engineering at Nylas, has to say: ‘While the benefits of cloud are clear, it can also be challenging to use it cost-efficiently over time. Our communications platform heavily utilizes cloud storage, and the associated API and at-rest costs were growing unsustainably, but we were concerned about the time, cost and risk to re-architect our platform. Since deploying Granica as our AI efficiency layer, we’re seeing a 10:1 reduction in our S3 API costs without any performance impact to our customers and without any re-architecting. What Granica offers is unique in the market and working with the Granica team is a game changer for our business.’”
“Quantum Metric provides the leading Continuous Product Design platform for companies to understand their customers’ digital journey, enabling organizations to recognize customer needs, quantify the financial impact, and prioritize tasks. We process 100 million objects per day for Quantum Metric, reducing their at-rest cloud storage costs by 40% on top of their custom-built gzip compression solution without archival or deletion. This is what Glenn Trattner, Chief Operating Officer at Quantum Metric, has to say: “At Quantum Metric, we are helping our customers regularly optimize their digital experiences and set the standard for what we call Continuous Product Design,” said Glenn Trattner, Chief Operating Officer at Quantum Metric. ‘Analyzing metrics to understand user workflows and behaviors while meeting real-time performance requirements entails an enormous amount of GCP storage and processing resources. For us to make the most of our hot data and keep up with exponential data growth, we had to solve for efficiency and drive down the cost of our unit economics. Since deploying Granica’s AI Efficiency Platform, we’re realizing a storage savings outcome of 40% on over 100 million objects per day of data, all while keeping the data secure and encrypted in our existing data stores. With Granica, we’ve prevented spiraling cloud costs while making our platform even more customer-centric.’”
Funding/Revenue
After asking Ponnala about funding/revenue, he revealed:
“Our total funding to date is $45 million from leading institutional firms including New Enterprise Associates (NEA), Bain Capital Ventures (BCV), Abstract Ventures, Uncorrelated Ventures, Original Capital, K9 Ventures, and Worklife, along with participation from several industry luminaries including former Tesla CFO Deepak Ahuja; Eventbrite Chairman and co-founder Kevin Hartz; and Frederic Kerrest, Executive Vice Chairman and co-founder, Okta. We currently do not disclose revenue metrics.”
Total Addressable Market
What total addressable market (TAM) size is Granica pursuing? Ponnala assessed:
“The TAM for Granica today is in the multiple billions of dollars. Data privacy alone, in which Granica Screen plays, is estimated at about $3 billion today, growing at a 40% CAGR. Granica Crunch also has a multi-billion dollar TAM driven simply by the savings potential of data reduction applied to the zettabyte scale size and fast growth of data globally. As we introduce more services onto our platform, the TAM for Granica will expand even further. Ultimately, we expect a TAM in the tens of billions of dollars that is compounding year-over-year.”
Differentiation From The Competition
What differentiates Granica from its competition? Ponnala affirmed:
“We are much more than a software vendor—we are an information and computer science company working on the hardest problems in data today. At its core, what we’re doing at Granica is fusing fundamental data-centric AI research with large-scale systems engineering expertise to build a platform that drives AI information density and efficiency at a cloud scale. Our research team – led by our chief scientist, Andrea Montanari, a pioneering expert in information theory and a professor at Stanford University – works in unison with our world-class engineering team, pushing the boundaries of data-centric AI to deliver first-to-market solutions that make AI affordable, accessible and safe to use.”
“Granica Crunch, our data reduction service, is the first of its kind in the world. For the vast majority of our customers, the nearest competition is “do nothing”. Some organizations choose to leverage archival tiers to lower their costs to store the data, but then they have much higher costs and waiting time to access that data. In the worst case, some are forced to simply delete data to control costs. Granica Crunch is the simplest and most secure way to significantly reduce the cost associated with storing and accessing petabyte-scale data without archival and/or deletion.”
“On the privacy front, traditional cloud-based DLP and data privacy solutions can help organizations comply with data privacy regulations, but such compliance represents a bare minimum for data security and does little to improve data security posture and mitigate the risk of serious data breaches. The low recall (i.e. high false negative rate) of traditional detection technologies leaves significant volumes of sensitive data undiscovered and unprotected. Further, existing solutions are only relevant once data has been persisted in cloud storage, and often after a significant delay. During that window, sensitive data is completely exposed. Worse, these solutions are too expensive to use on large-scale unstructured data sets. As a result, organizations are forced to scan only a small, sampled subset. They then apply statistical methods and follow-up scans in the hopes of achieving a semblance of data privacy.”
“In contrast, Granica Screen plugs inline into applications, detecting and protecting new, incoming sensitive data with high precision and recall before it is ever persisted in a cloud object store, thus dramatically increasing data security posture and mitigating breach risk while also preserving privacy for AI/ML training. Screen also works with existing data, providing comprehensive data privacy coverage. Finally, Screen is highly compute-efficient, lowering the cost to scan data by 10x and enabling our customers to scan and protect all their data, not just a sample.”
Future Company Goals
What are some of Granica’s future company goals? Ponnala pointed out:
“From my initial foray into image processing in 2006 to the launch of Granica in 2023, this journey has been both fascinating and transformative. The challenges of extracting valuable information from byte streams and preserving integrity while optimizing use led our team to create a platform that addresses these issues head-on. But Granica is more than just an answer to these challenges—it’s a visionary step towards a future where every company, irrespective of its size, can leverage the power of AI effectively and efficiently.”
“We’re not merely selling a service. We’re offering a new way of doing business, a path that melds affordability, security, and seamlessness into the fabric of AI applications. With Granica, our customers don’t just adapt to the AI revolution—they lead it.”
“With Granica Crunch, Granica Screen, and Granica Chronicle we’ve showcased what is possible when advanced information science meets innovative engineering. But this is just the beginning. We have exciting innovations in the research and development stages that we will deploy in 2023 and 2024. We’re committed to pushing the boundaries, expanding the realm of the possible, and creating pathbreaking solutions that drive AI Efficiency forward. At Granica, AI efficiency is not just a goal—it’s our DNA. It’s a place where we don’t just navigate the future of AI—we shape it, one byte at a time.”
Additional Thoughts
Any other topics to discuss? Ponnala concluded:
“We’re growing fast and looking for the best-of-the-best researchers and engineers who want to work on fundamental problems. We strive to create an environment where customers are our obsession, results are achieved, efficiency is valued, diversity and inclusion thrive, iteration leads to progress, and teamwork is the foundation of our success. Granica is for people who not only relish the challenge of solving complex problems, but thrive on it, and we invite them to join us and play a lead role in the next exciting chapter of our story. We’re in this for the long haul, are relentlessly ambitious, and will not stop until we build an iconic company in the world.”
