Granica recently emerged from stealth and introduced the industry’s first AI efficiency platform, bringing novel and fundamental research in data-centric AI to the commercial market as an enterprise solution. And the company’s cloud-native solution operationalizes a next-generation approach to AI efficiency via data reduction and data privacy, enabling AI teams using Amazon S3 and Google Cloud Storage (GCS) to derive maximum value from their ever-growing volumes of training data.
Granica makes it easier for more AI data to be cost-effectively captured, stored, and used to power enterprise AI implementations and improve model performance and business outcomes. Utilized as an API, Granica physically reduces the size and cost of petabyte-scale AI training data in cloud object stores by up to 80% by using novel compression and deduplication algorithms. Granica also preserves the privacy of sensitive information in object data, enabling its safe use in AI and analytics while improving data security posture.
At launch, Granica is focused on efficiency for data with a goal of driving efficiency across the end-to-end AI pipeline. And for the first time, C-level executives in data-intensive industries can drive significant profitability and innovation gains by pursuing AI efficiency, complementing their existing efficiency initiatives.
The company’s outcome-based pricing model only charges users a small percentage of the savings generated per month (and only if savings are generated) so that deployment of the solution delivers upside only.
Founded by CEO Rahul Ponnala and CTO Tarang Vaish – who are seasoned data experts and former engineers at Pure Storage and Cohesity – Granica’s total funding to date is $45 million from leading venture capital firms New Enterprise Associates (NEA), Bain Capital Ventures (BCV) and others 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.
The inefficiency in AI is driven largely by the rapid proliferation of training data with low information value. And such data often contains significant redundancy and sensitive information, including personally identifiable information (PII). This information inefficiency increases costs, risks, and the time it takes for teams to move data through the AI pipeline.
Through a cloud service provider-native infrastructure, the Granica AI Efficiency Platform integrates inline with cloud applications, making data as well as downstream pipelines and models more efficient, more performant and privacy preserving. And Granica Crunch – which is the company’s data reduction service – eliminates redundant and low-value data, cutting costs and speeding up downstream processes for hot AI data. And Granica Screen, the company’s data privacy service, enables organizations to safely leverage sensitive data for AI and business use cases while improving their data security posture and reducing breach risk. As Granica is continuing on its mission to build the de facto standard for AI efficiency, data trust and collaboration, additional services and products will be brought to market to provide companies with end-to-end AI efficiency and new ways to maximize ROI on AI.
Granica Crunch is known as the data reduction service for enterprise AI. And it provides Byte-granular Data Reduction containing novel compression and deduplication algorithms which losslessly reduce the physical size of enterprise AI training data like sensor, image and text files, reducing costs to store and transfer objects in Amazon S3 and GCS by up to 80%. And it reduces write costs by up to 90% by intelligently batching write requests and optimizing other storage operations.
Granica Screen is known as the data privacy service for enterprise AI. And it provides Byte-precise Detection for both high recall and high precision identification and protection of sensitive data, including PII contained in structured, semistructured and unstructured text data. Granica Screen also enables enterprises to improve their data security posture and prevent breaches, safely use their data for AI and analytics use cases, and simplify regulatory compliance. Plus it is built to enable privacy-enhanced computing. Granica Screen is available via an Early Access Program.
Granica’s revolutionary business model is focusing on delivered outcomes as opposed to mere consumption. And the platform is free to deploy with no upfront costs. After deployment, Granica measures how Crunch reduces storage costs relative to the Amazon S3 and GCS baseline. The cloud costs incurred in the user’s environment is then covered by the generated baseline savings, resulting in a savings outcome for the user. And Granica customers simply pay Granica a small portion of the savings outcome.
Granica’s pricing model is new to the AI industry and provides the ultimate customer-centric solution. The benefits include:
— Pay only for the value received
— No financial risk to try or to expand usage
— No need to find or allocate budget
— No need for a complicated total cost of ownership (TCO) modeling
— Easy to forecast future savings for reinvestment into AI data, people and tooling
KEY QUOTES:
“The sheer volume of data required to properly train AI models makes responsible and performant AI out of reach for many organizations. Granica democratizes access to AI while keeping data secure — to make AI more accessible, affordable and safe to use. Granica’s fusion of novel research and systems engineering places the company in a strong position to lead the new wave of data-centric AI.”
— Pete Sonsini, investor at NEA
“Our mission is to enable enterprise AI teams to maximize the value of their data and keep much more, if not all, of their AI data ‘hot.’ This is the key to unlocking the transformative potential of artificial intelligence and machine learning. Data fuels the AI engines that are quickly becoming essential to modern commerce, science and everyday life. Just look at the sudden explosion in generative AI tools to get a sense of the future reach of this technology.”
“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. Building a technology company that solves hard problems requires empowering brilliant people as much as commercializing cutting edge research. We take pride in our people-centric approach to our organization.”
“Instead of charging users based on consumption, we measure and charge for the outcomes Granica’s efficiency services deliver within the customer’s environment. Companies no longer have to run up against an ‘innovation wall’ due to sky-high cloud compute and cloud storage costs. The amount saved from using Granica puts dollars right back into organizations’ AI-based innovations—or directly to their bottom line. Simply put, Granica’s incentives to drive AI efficiency are aligned with our customers. The more value we can deliver from every byte of data, the more our customers improve their ROI on AI, and the more we earn. It’s a total win-win.”
— Rahul Ponnala, co-founder and CEO of Granica
“There is a huge efficiency gap for AI workloads, especially for training data in cloud object stores like Amazon S3 and Google Cloud Storage. Making data more efficient requires an entirely new layer in the AI stack consumed as an API and directly integrated with AI applications. 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 cloud scale.”
— Andrea Montanari, chief scientist at Granica
“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 have allowed us to reallocate investments back into our business.”
— Jason Fuller, head of cloud and employee foundations at HERE Technologies
“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.”
— John Jung, vice president of engineering at Nylas
“At Quantum Metric, we are helping our customers regularly optimize their digital experiences and set the standard for what we call Continuous Product Design. 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.”
— Glenn Trattner, chief operating officer at Quantum Metric
“Modern organizations in nearly every industry sector depend on leveraging their rapidly growing data in the cloud to drive business innovation. However, many are finding that cloud data spending can quickly spin out of control. Here at the FinOps Foundation, we work with companies in establishing a FinOps culture that prioritizes cloud cost transparency, which enables organizations to get the most value out of their cloud spend. Platforms like Granica automate efficiency optimizations, providing more value while helping to reduce the effort required by engineering teams. We’re excited to see Granica advance the concept and practice of data efficiency as it addresses an unmet need in the market.”
— Mike Fuller, CTO at the FinOps Foundation
“At GlobalDots, we’re always on the hunt for cutting-edge cloud technologies that help achieve cost reduction for a variety of businesses — from rising startups to advanced enterprises and everyone in between — especially as spiraling cloud costs are the number one challenge in today’s ecosystem. We chose to partner with Granica, adding its capabilities to our innovative FinOps portfolio, as they enabled us to unlock cost-saving capabilities in AI/ML pipelines and object storage — two significant areas where cost reduction was previously inaccessible. With Granica, we’re able to expand our Cloud Financial Management capabilities. We’re engaged with numerous customers, achieving great success together. Our goal is to spread Granica’s platform all over EMEA and make it the de-facto standard for accessing cloud storage for AI and other data intensive workloads.”
— Thorsten Deutrich, vice president of sales and DACH regional manager at GlobalDots
