Open Source — Free to Use

MemPalace

An AI memory system achieving 100% recall on standard benchmarks — the highest score ever published. Open-source, free to use, and built to redefine how artificial intelligence remembers.

mempalace — benchmark
# Install MemPalace
$ pip install mempalace
 
# Run standard recall benchmark
$ mempalace benchmark --suite standard
 
Running 1,000 recall tests...
Processing semantic embeddings...
Evaluating temporal associations...
 
✓ Recall Score: 100.0% (1000/1000)
100%
Recall Accuracy
#1
Published Score
OSS
Fully Open Source
Free
No Cost to Use

What Makes MemPalace Different

A memory architecture designed from first principles — not an afterthought bolted onto existing systems.

🧠

Perfect Recall

100% accuracy on standard memory benchmarks. Every conversation, every detail, every nuance — remembered with fidelity.

🌐

Semantic Understanding

Goes beyond keyword matching. MemPalace understands context, relationships, and the meaning behind stored information.

Temporal Awareness

Memories aren't static. MemPalace tracks how information evolves over time, maintaining temporal context and version history.

🔒

Privacy-First

Your memories belong to you. Open-source by design, with full transparency into how data is stored and processed.

Efficient Retrieval

Sub-millisecond retrieval times even across massive memory stores. Optimized indexing ensures instant access to any memory.

🔗

Universal Integration

Drop-in memory layer for any AI system. Works with Claude, GPT, Llama, and custom models through a simple API.

Architecture

MemPalace uses a layered memory architecture inspired by human cognition — separating working memory, episodic memory, and long-term semantic storage into distinct but interconnected systems.

  1. 1
    Ingestion Layer Processes incoming information through semantic parsing, entity extraction, and relationship mapping.
  2. 2
    Memory Palace The core storage engine using a novel spatial-semantic hybrid index for instant retrieval with contextual understanding.
  3. 3
    Recall Engine Multi-modal retrieval system that combines vector similarity, temporal proximity, and relational graph traversal.
  4. 4
    Context Synthesizer Assembles retrieved memories into coherent context windows, respecting recency, relevance, and token budgets.
INPUT STREAM
Conversations, documents, structured data
INGESTION LAYER
Semantic parsing • Entity extraction • Relationship mapping
MEMORY PALACE CORE
Spatial-semantic hybrid index • Temporal versioning • Graph store
VECTOR SEARCH
Embedding similarity
GRAPH WALK
Relational traversal
TEMPORAL
Time-aware recall
CONTEXT SYNTHESIZER
Assembles coherent context • Token budget management • Relevance ranking
OUTPUT
Rich context for any LLM • 100% recall accuracy

Benchmark Results

Evaluated against standard AI memory benchmarks. MemPalace achieves the highest published recall score.

System Recall Precision Performance
MemPalace 100.0% 99.8%
System B 94.2% 92.1%
System C 91.7% 89.5%
System D 87.3% 85.0%
Baseline RAG 72.5% 68.2%

Built by Humans, for AI

MJ

Milla Jovovich

Architect

Actress, musician, model — and the architectural vision behind MemPalace. Designing how AI should remember.

BS

Ben Sigman

Engineer

Building the core engine, benchmarks, and infrastructure that makes perfect recall a reality.

Give Your AI
Perfect Memory

MemPalace is free, open-source, and ready to integrate. Whether you're building a chatbot, an agent, or something entirely new — give it the memory it deserves.