Accelerate AI Inference With Intelligent Context Memory
Reuse KV Cache across requests, GPUs, and infrastructure to reduce TTFT, increase token throughput and GPU efficiency.
Transform the Economics of Distributed Inference at Scale
Our Vision
Who We Serve
The Problem
Make memory a first-class infrastructure layer for AI inference
As AI moves toward longer context, reasoning, RAG, and agentic workloads, efficiently managing and reusing context becomes critical. TensorMem's intelligent memory infrastructure layer orchestrates working memory (KV Cache) across memory tiers and across distributed inference—making it faster, more scalable, and more efficient.
The Problem
Who We Serve
The Problem
AI Inference Recomputes Too Much
As context windows grow and workloads become more agentic, inference repeatedly processes the same or overlapping context. Valuable computed state is trapped in limited GPU memory or discarded, forcing expensive recomputation. Reusing this state reduces TTFT, increases token throughput, improves GPU efficiency, and lowers inference cost at scale.
Who We Serve
Who We Serve
Who We Serve
Built for AI Inference at Scale
We serve AI clouds and neo-clouds, inference platforms, serverless inference providers, enterprises, and AI infrastructure providers. Wherever long-context, RAG, reasoning, or agentic workloads demand higher throughput and better GPU efficiency, TensorMem helps make inference faster and more economical.
Completely software-defined. No new hardware!
Founding Team & Advisors
Anand Kekre (Co-founder)
IIT Bombay graduate, serial entrepreneur with two successful startup exits and 67 US patents. Former Chief Architect and CTO at VERITAS and Arctera, with prior experience at IBM and McAfee. Deep expertise in distributed software-defined storage, infrastructure, cyber resilience, and cloud-scale enterprise solutions. Three decades of experience building and leading mission-critical distributed systems from early architecture through large-scale production.
Arvind Pande (Co-founder)
IIT Kharagpur graduate, 15 US patents, and founding engineer of MapR Technologies — a pioneering distributed data platform for large-scale analytics. Previously held engineering roles at VERITAS, Symantec, and ServerEngines. Deep expertise in high-performance data infrastructure and hyper-scalable enterprise solutions. Over 25 years of experience architecting and building distributed systems for demanding enterprise and cloud-scale workloads.
Fred van den Bosch (Advisor)
A private investor, business consultant, and experienced technology executive. His career spans the architecture and design of complex hardware and software systems, as well as leadership roles including CEO, CTO, and Executive Vice President of Engineering. He previously served on the Board of Directors of VERITAS Software and currently serves as a Director of Varonis Systems, Inc., as well as a board member and advisor to several private companies.
Srinivasan "Sesh" Seshadri (Advisor)
Srinivasan “Sesh” Seshadri is a three-time founder (Zettata, Kosmix, and Strand Life Sciences) with successful exits and a veteran of database and distributed systems, with 30+ years across academia, startups, and large companies. Most recently, he was Chief Innovation Officer at Aerospike. He has also held senior roles at Google and Bell Labs and was a computer science faculty member at IIT Bombay. Sesh holds a PhD from UW-Madison and a B.Tech from IIT Madras, and has 50+ publications and 15 issued patents in databases and data systems.
Bijayalaxmi Nanda (Founding Member)
Indian Institute of Science (IISc) graduate with 25+ US patents and over two decades of engineering experience in distributed systems and cloud storage across Microsoft, Dell EMC, Symantec, and VERITAS. Prior to TensorMem, Bijaya was with Microsoft Azure Storage, where she led key architecture, performance, and operational safety initiatives for ADLS Gen2, supporting large-scale enterprise analytics and AI workloads.
Gary Garcia (VP - Strategic Alliances)
Gary Garcia brings extensive experience building strategic alliances, partner ecosystems, and go-to-market programs for enterprise technology companies. At NetApp, he led the development and launch of FlexPod, the partner-enabled NetApp and Cisco solution. At Arm, he led the Mbed Partner Program. Earlier at VERITAS, Gary built the Defense 360 partner program and developed strategic alliances, including OEM technology licensing agreements with SAP and HP.
Investors
We are backed by "Venture Guides", and experienced technology leaders and angel investors from Google, VERITAS, VMWare, Netflix, NetApp and many other leading infrastructure companies.
About TensorMem
TensorMem Inc. is a Delaware C-Corp building a software-defined context-memory orchestration platform for high-performance inference, powered by an AI-native distributed caching and storage layer.
As inference becomes the dominant driver of AI economics, TensorMem addresses the growing challenge of managing KV Cache and data movement across the memory–storage hierarchy.
Built on deep expertise in distributed systems, enterprise storage, databases and resiliency, TensorMem provides a foundational layer for efficient, scalable AI inference that works across models, inference servings and hardware platforms.
