
Granica is a pioneer in AI-driven data optimization, delivering state-of-the-art technologies to help enterprises manage large-scale data volumes used in AI, machine learning, and…

Granica is a pioneer in AI-driven data optimization, delivering state-of-the-art technologies to help enterprises manage large-scale data volumes used in AI, machine learning, and…
Headquarters: Mountain View, California
Founded: 2019
Core product: Crunch — high-performance data compression for AI workloads
Total funding: USD 45,000,000
Team size (reported): 38 employees
Data readiness and optimization for large-scale AI/ML workloads, including compression, privacy/safety, and dataset curation.
2019
Software Development
Company profiles report at least one institutional Series A round; multiple investors are listed across profiles.
“Backed by institutional investors including Bain Capital Ventures, NEA, K9 Ventures, Abstract Ventures, Original Capital, and Uncorrelated Ventures; angel/backers reported include Deepak Ahuja, Kevin Hartz, and Frederic Kerrest.”
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About Granica Granica is an AI research and infrastructure company focused on reliable, steerable representations for enterprise data.
We earn trust through Crunch , a policy-driven health layer that keeps large tabular datasets efficient, reliable, and reversible. On this foundation, we’re building Large Tabular Models —systems that learn cross-column and relational structure to deliver trustworthy answers and automation with built-in provenance and governance.
The Mission AI today is limited not only by model design but by the inefficiency of the data that feeds it. At scale, each redundant byte, each poorly organized dataset, and each inefficient data path slows progress and compounds into enormous cost, latency, and energy waste.
Granica’s mission is to remove that inefficiency. We combine new research in information theory , probabilistic modeling , and distributed systems to design self-optimizing data infrastructure: systems that continuously improve how information is represented and used by AI.
This engineering team partners closely with the Granica Research group led by Prof. Andrea Montanari (Stanford), bridging advances in information theory and learning efficiency with large-scale distributed systems. Together, we share a conviction that the next leap in AI will come from breakthroughs in efficient systems, not just larger models.
What You’ll Build
What You Bring
Bonus
Why Granica
Compensation & Benefits
At Granica, you will shape the fundamental infrastructure that makes intelligence itself efficient, structured, and enduring. Join us to build the foundational data systems that power the future of enterprise AI!
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