Turn LMCache into a production-ready stack with our full suite of enterprise tools.
Stop letting VRAM limits dictate your context length. Tensormesh intelligently manages your KV-cache across three high-performance storage layers.
Immediate execution for active tokens.
Sub-second retrieval for hot contexts and multi-turn loops.
Persistent storage for
massive RAG libraries and long-
document personas.
While LMCache is the engine, Tensormesh is the control plane. We provide the operational tools required for AI production.
Real-time visibility into cache hit rates, throughput, cost savings, and infrastructure health across your entire deployment.
Built for mission-critical workloads with automatic failover, redundancy, and continuous monitoring for zero-downtime operations.
Enterprise-grade security with data encryption, access controls, and compliance-ready architecture for sensitive workloads.
Access 300,000+ open-weight models from Hugging Face, Qwen,
Kimi, and Mistral AI without changing your stack.
Whether you're orchestrating multi-agent systems, retrieving context for RAG, or managing multi-round conversations, Tensormesh eliminates the 'Amnesia Tax' across all AI workloads.
Multi-agent systems waste compute on duplicate context and repeated tool calls. Tensormesh caches shared state across agents, eliminating redundant work and accelerating orchestration.
RAG applications repeatedly retrieve and process the same documents. Tensormesh caches document context and query results, delivering instant responses while slashing the cost of long-context processing.
Conversational agents shouldn't recompute the entire dialogue history on every turn. Tensormesh caches conversation state across rounds, enabling seamless multi-turn interactions at a fraction of the GPU cost.
Connect Tensormesh to your stack via our OpenAI-compatible API. We sit between your users and inference engines, transparently caching and optimizing every request.
Our system automatically identifies redundant prefixes in your traffic. Whether it's a 100k-token document or a repetitive system prompt, Tensormesh captures the KV-cache and intelligently distributes it across your cluster for optimal performance.
When matching context is detected, your GPU skips the expensive prefill phase. The system streams cached state into VRAM, and the model starts generating new tokens instantly.
Connect Tensormesh to your stack via our OpenAI-compatible API. We sit between your users and inference engines, transparently caching and optimizing every request.
Our system automatically identifies redundant prefixes in your traffic. Whether it's a 100k-token document or a repetitive system prompt, Tensormesh captures the KV-cache and intelligently distributes it across your cluster for optimal performance.
When matching context is detected, your GPU skips the expensive prefill phase. The system streams cached state into VRAM, and the model starts generating new tokens instantly.
Created by
Friday Marketing Agency
