Miruvor
Human Memory for AI.
Neural Memory Infrastructure for AI Agents and Robots to help them Remember and Recall like Human Brains.
Integration So Simple,
It's Almost Unfair
from neuralmem import MemoryAgent
agent = MemoryAgent(api_key="your_key")
agent.remember("user_123", "loves pizza")
memory = agent.recall("user_123")
# Returns: "loves pizza"What is Neuromorphic
Context Engineering?
Neuromorphic Context Engineering dynamically assembles and activates only the most relevant memories, relationships, and temporal patterns around a spiking neural network, delivering hyper-personalized, biologically-plausible responses in real time.
Unlike traditional vector + prompt stuffing, Miruvor doesn't just retrieve text, it activates living, adaptive neural circuits that evolve with every interaction, preserving chronology, causality, emotions, and long-term user identity at the hardware-neuron level.
Traditional agents forget who you are after 4K tokens.
Miruvor remembers you forever, like a real brain.
AGENT FRAMEWORK
Miruvor Agent Core
NEUROMORPHIC CONTEXT ENGINEERING
Fractal-Temporal Activation
Infinite Spiking Long-Term Memory
Dynamic Synaptic Knowledge Graph
Reservoir Attractor Search
Wave-Propagated Context Assembly
Tool Integration
LLM
Hybrid LLM Readout (optional)
How Miruvor Works
Spiking Network Construction
Automatically extract and encode entities, relationships, and facts from conversations into neural networks, reconciling new information with existing patterns to maintain accuracy.
Associative Spike Retrieval
When your agent needs context, Miruvor propagates query spikes through the network and returns the most relevant activations via attractor convergence.
Neural Context Assembly
Miruvor delivers structured, ready-to-use context by combining user traits, interactions, and data while maintaining spike efficiency (no token limits).