Granica emerged from stealth today and introduced the industry's first AI efficiency platform, bringing novel, fundamental research in data-centric AI to the commercial market as an enterprise solution. 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 feasible for more AI data to be cost-effectively captured, stored and used to power enterprise AI implementations and thereby improve model performance and business outcomes. Consumed as an API, Granica physically 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. Granica also preserves 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. 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.

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.

Granica is the world's first AI efficiency platform. 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. Powered by novel compression and deduplication algorithms, its byte-granular inline data reduction of petabyte-scale sensor, image and text AI training data runs transparently in the background, losslessly reducing AI data costs by up to 80%. Granica also provides privacy preservation for PII and other sensitive information, unlocking valuable data for safe use in downstream AI workflows. Granica's AI efficiency services are easily consumed as an API by developers building applications that access AI data in public cloud object storage platforms such as Amazon S3 and Google Cloud Storage.