Press release

Enterprise AI Go-To-Market Leader Joins AI Efficiency Innovator Granica as SVP of Revenue

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Granica, the world’s first AI efficiency platform, announced today that Jay McGrath joined as Senior Vice President of Revenue. At Granica, Jay will lead global go-to-market efforts across the sales, solutions engineering and customer success functions and will build the company’s revenue operations processes and toolset.

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Granica, the world’s first AI efficiency platform, announced today that Jay McGrath joined as Senior Vice President of Revenue. (Photo: Business Wire)

Granica, the world’s first AI efficiency platform, announced today that Jay McGrath joined as Senior Vice President of Revenue. (Photo: Business Wire)

Prior to joining Granica, Jay held various sales leadership roles at UiPath, a leading Robotic Process Automation provider where he helped establish the U.S. sales organization, scaling U.S. revenues from $500,000 to over $250 million in just over four years. This growth contributed to the company’s successful $36 billion IPO in 2021, making it one of the largest and most valuable tech IPOs ever. In his most recent role as Chief Revenue Officer at Tonkean, a no-code automation platform, Jay rebuilt the sales team and go-to-market function, doubling the company’s customer base within 12 months.

“I’m truly ecstatic to announce Jay McGrath as the newest member of our leadership team here at Granica. His addition is a testament to our vision and culture as a customer-obsessed AI research and deployment company,” said Rahul Ponnala, co-founder and CEO of Granica. “As SVP of revenue, Jay will be in charge of all things related to our go-to-market efforts, bringing our cutting-edge AI efficiency solutions to our customers worldwide via sales motions centered on customer-value and tangible results. With our ever-stronger leadership bench, we are well on our way to solidifying our mission to bring AI efficiency and safety to every enterprise.”

“Data fuels organizational decision-making. With the recent trends in AI, enterprises will come to rely on these tools to make the most out of their data — but we’re at an inflection point. AI models can only be useful if the data they rely on is accurate and secure,” said McGrath. “I joined Granica because its platform is designed to allow more data to be cost-effectively captured, stored and used to power enterprise AI implementations, thereby improving AI model performance and business outcomes. The team is hyper-dedicated to the mission, with a strong culture focused on teamwork and inclusion. I’m excited to work with this amazing group to help our customers break down the barriers to AI innovation, dramatically lower their costs and increase data security.”

Granica launched from stealth earlier this month and introduced the industry’s first AI efficiency platform. Jay’s role will be instrumental in operationalizing the company’s mission to help make AI affordable, accessible and safe for everyone to use.

Additional Resources

About Granica

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. It’s the simplest and most secure way for businesses to cut the costs of AI training data without the severe trade-offs associated with archival or deletion. Improving the efficiency of AI data and pipelines puts the focus back on model performance. Outcome-based pricing whereby organizations only pay Granica a small percentage of their realized savings eliminates the need for upfront budgeting and investment and ensures enterprises only receive upside. Granica is optimized for data and AI-intensive industries such as geo-spatial intelligence, autonomous vehicles, robotics, retail and ecommerce. Category-defining companies including HERE Technologies, Quantum Metric and Nylas use Granica to cost-effectively keep, grow and use their AI data to maximize innovation and business results from their AI initiatives.