Palo Memory Engines & Use Cases
Revolutionary episodic memory systems that enhance any LLM, chatbot, or robot with humanlike memory capabilities. Explore our models and their applications.
Reimagining Memory for AI
Mpalo's Palo models represent a fundamental shift in how AI systems remember and understand context. Unlike known RAG approaches that search for relevant information, our episodic memory system mimics human memory patterns, creating more natural, accurate, and meaningful interaction.
Why Episodic Memory Matters
Conventional AI systems struggle with maintaining context over long conversations. Our approach doesn't just retrieve information, it understands experiences and interactions contextually, just like humans do.
- Maintain memory across different conversations
- Process both text and visual information naturally
- Develop truly personalized interactions based on shared history
- Eliminate repetitive information requests from users
The Mpalo Difference
Our modular approach lets you enhance any AI system with Palo memory capabilities without replacing your existing infrastructure.
- Simple integration with any LLM or Robot
- API-first design for maximum flexibility
- User friendly browser-extension for Website Chatbots
- Support for both your own private vector stores (BYOVS) and our managed Private Data Spaces.
- Close to humanlike memory patterns, not just search functionality
Keep In Mind: Modes of Operation
All engines come with either a Personalization Mode, which offers humanlike blurry memory and forgetting, or a Research Mode that aims to enhance accuracy, knowledge breadth, and depth while ensuring that important details are not forgotten.
Lightweight Memory Solutions
Our efficient memory models designed for speed and accessibility, perfect for consumer applications and development environments.

Palo Mini
Our entry-level memory model offering essential contextual memory for everyday applications. Perfect for chatbots and lightweight consumer-facing applications where speed matters and resources are limited.
Ideal Use Cases:
- Customer support chatbots
- Personal assistant apps
- Adaptive educational tools
- E-commerce preference recall
Technical Features:
- Low latency
- Basic text memory
- Cost-effective

Palo Bloom
A balanced solution offering enhanced memory capabilities with minimal latency impact. Ideal for developer environments and applications requiring more advanced memory features.
Ideal Use Cases:
- Multilingual customer service
- Content creation style recall
- Healthcare interaction history
- Contextual code understanding
Technical Features:
- Optimized performance/capability
- Enhanced text, basic image memory
- Multilingual support
Memory Management & Ethics
Mpalo is committed to responsible memory management. All Palo models include advanced mechanisms to ensure ethical, efficient, and privacy-preserving memory operations.
Intelligent Forgetting
Our DEEP models implement cognitive science-based forgetting mechanisms to prevent memory overload while preserving essential information.
Features:
- Importance-weighted retention
- Temporal decay patterns
- Automatic summarization
- Memory consolidation
Privacy & Ethics Controls
Our commitment to ethical AI means comprehensive controls for managing memory with user privacy and consent at the forefront.
Features:
- Selective memory purging
- Explicit consent management
- Configurable retention
- Privacy-preserving encryption