Granica is an AI research and systems company helping enterprises leverage AI efficiently and safely. Our mission is to make AI 10,000x better. We believe data is the first-mile problem to solve in this mission. 

Our first system is a novel training data platform for enterprise AI that unlocks efficiency and privacy through our flagship services tailored for Generative and Traditional AI:

Granica Crunch is a family of advanced data compression/reduction models which enable AI/ML teams to add and use more data to improve their ML accuracy and performance while controlling their infrastructure costs. Crunch delivers deep cost efficiencies for data at any scale, at rest and in use.

Granica Screen is an advanced data privacy-enhancing service that  unlocks even more data for AI/ML teams to safely improve model performance. It guarantees state-of-the-art privacy at scale, enabling Private LLMs and Privacy-preserving AI.

Granica Chronicle is a deep data visibility service for disparate AI data stores. Enabling unification, collaboration and insights into data usage for AI and ML.

Our research is deeply rooted in information science, machine intelligence, computer vision, natural language, and distributed systems, with a special emphasis on elevating the efficiency and safety of AI systems through fundamental and innovative research.

We're backed by remarkable institutional investors in AI, Data, and Cloud; and several industry luminaries in business and technology.

AI/ML

Data

Granica

Rahul Ponnala

Mack Yi

Jason Nadeau

Diego Acosta

Andrea Montanari

Tarang Vaish

The Engineering Team at Granica is responsible for the design, development, and deployment of cutting-edge AI systems and platforms. They build and optimize advanced data compression models (Granica Crunch), ensure robust data privacy enhancements (Granica Screen), and develop tools for deep data visibility and collaboration (Granica Chronicle). Their work is pivotal in elevating AI efficiency and safety, solving complex problems in machine intelligence, computer vision, natural language processing, and distributed systems. The team collaborates closely to innovate and implement solutions that drive enterprise AI advancements.

Engineering Team

Leadership Team

Engineering Team

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Engineering Team

Leadership Team