Artificial intelligence efficiency platform startup Granica launched out of stealth mode today with a platform designed to help petabyte-scale Amazon Web Services Inc. S3 and Google Cloud Storage customers eliminate redundant and low-value data.

Claimed to be the industry’s first AI efficiency platform, Granica’s platform is said to bring novel, fundamental research in data-centric AI to the commercial market as an enterprise solution. The company’s solution puts into operation a next-generation approach to AI efficiency via data reduction and data privacy, enabling AI teams using AWS S3 and Google Cloud Storage to derive maximum value from their growing volumes of training data, according to the company.

Granica’s platform is designed to allow more AI data to be cost-effectively captured, stored and used to power enterprise AI implementations, thereby improving model performance and business outcomes. Implemented as an application programming interface, Granica reduces the size and cost of petabyte-scale AI training data in cloud object stores by up to 80% using novel compression and deduplication algorithms.

The service 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 plans to drive efficiency across the end-to-end AI pipeline.

Granica launches with funding of $45 million from New Enterprise Associates Inc., Bain Capital Ventures Partners LLC and several individual investors, including former Tesla Inc. Chief Financial Officer Deepak Ahuja, Eventbrite Inc. Chairman and co-founder Kevin Hartz and Frederic Kerrest, co-founder and executive vice chairman of Okta Inc.

“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,’” Rahul Ponnala, co-founder and chief executive officer of Granica, said in a statement. “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.”

Pricing for the service is unique, with Granica offering an outcome-based pricing model that 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.

Granica measures the cost savings achieved by customers using its service each month. The savings could come from a reduction in storage needs, lower data transfer costs, or increased efficiencies in AI training processes. Granica then charges a small percentage of these savings as its fee.

“Companies no longer have to run up against an ‘innovation wall’ due to sky-high cloud compute and cloud storage costs,” Ponnala explained. “The amount saved from using Granica puts dollars right back into organizations’ AI-based innovations — or directly to their bottom line.”

Photo: Granica