Miruvor

Human Memory for AI.

Neural Memory Infrastructure for AI Agents and Robots to help them Remember and Recall like Human Brains.

Neural Memory Encoding
Advanced neural integration techniques that encode memories with unprecedented efficiency, mimicking the brain's natural plasticity and retention mechanisms.
Contextual Intelligence
Seamlessly integrates with your daily workflow, understanding context and relationships to provide intelligent memory recall when you need it most.
Seamless Integration
Connect with your existing tools and workflows. Miruvor adapts to your environment, making memory enhancement effortless and natural.
AI-Driven Optimization
Continuously learns and optimizes memory storage and retrieval patterns, ensuring your most important information is always accessible.

Integration So Simple,

It's Almost Unfair

QUICK_START.PY
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

MIRUVOR NEUROMORPHIC CAPABILITIES

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

Watch how conversations become living neural memories

Ready
Spiking Neural Network15 neurons • 21 synapses

Memories

Memories will appear here...
1

Spiking Network Construction

Conversations are encoded as spike patterns, forming a living neural network that preserves relationships and temporal context.

2

Associative Spike Retrieval

Queries propagate through the network as spikes, activating relevant memories through biological attractor dynamics.

3

Neural Context Assembly

Activated memories are assembled into structured context — no token limits, just relevant information delivered instantly.

Traditional AI:4K token limitMiruvor:Infinite memory

Let Your AI Remember Forever