PyTorch Memory Enterprise
GPU-accelerated semantic search. Sub-2ms. Every time.
PyTorch Memory is vector search that runs on your GPU. Not a cloud service you pay monthly - infrastructure you own.
Load once, search instantly, scale to millions of vectors.
The Problem: Cloud vector databases mean latency, recurring costs, and your data on someone else's servers. Local
alternatives are slow or complex to deploy.
The Solution: PyTorch Memory runs on your hardware. RTX 3090? Sub-2ms search across 2,500+ vectors. Scales with your
GPU. Your data never leaves your machine.
Performance:
• Sub-2ms semantic search (GPU-dependent)
• 847+ memories loaded in under 2 seconds
• CPU fallback when GPU unavailable
• Checkpoint system - no cold start penalty
What's Included:
• Full source code
• Docker configuration (CUDA-enabled)
• MCP server for Claude Desktop
• Python SDK with examples
• 1 year updates
Requirements: Python 3.10+, PyTorch, CUDA-capable GPU (or CPU fallback)
⚡ PyTorch Memory Enterprise GPU-Accelerated • Production Scale $600 Base license (1 developer) +$60 per additional developer • Sub-2ms semantic search (GPU-dependent) • CUDA + CPU fallback included • Docker deployment with NVIDIA toolkit • MCP server (open protocol) • Full source code • 1 year updates 90-day money-back guarantee. See EULA for full terms.