Understanding M-Maze's core architecture
M-Maze is a revolutionary memory-augmented AI assistant that transforms how AI systems interact with users by maintaining long-term memory and context awareness. Unlike traditional chatbots that start each conversation from scratch, M-Maze remembers your preferences, conversation history, and personal information through our advanced IMDMR technology.
M-Maze uses Intelligent Multi-Dimensional Memory Retrieval (IMDMR) technology to provide context-aware, personalized responses based on your entire conversation history. This 6-step process makes every interaction intelligent and personalized.
Every message you send is analyzed using AWS Bedrock to extract key information like names, professions, locations, and interests. This creates a rich understanding of what you're sharing.
M-Maze determines what you're trying to achieve - whether you're introducing yourself, asking questions, or sharing information. It understands conversation flow and references.
Your information is stored in our Qdrant vector database across multiple dimensions: semantic meaning, time, entities, categories, and quality scores. This enables intelligent retrieval.
When you ask questions, M-Maze analyzes your query and selects the best search strategy: entity-based, category-based, semantic similarity, or context-aware search.
Using multiple search strategies, M-Maze finds the most relevant memories, ranks them by relevance and quality, and provides context-aware information retrieval.
Finally, M-Maze generates personalized responses using AWS Bedrock Llama 3, incorporating retrieved memories to maintain conversation continuity and provide personalized insights.
Even though the chat interface shows a fresh start each time you log in, the IMDMR system maintains all your conversation context in the backend. When you chat, M-Maze processes your messages through these 6 steps, creating intelligent, personalized responses that remember everything about you while providing a clean, focused user experience.
Complete technical architecture of the IMDMR-powered M-Maze system
User message received via FastAPI endpoint
Entity extraction & intent classification
Vector embedding generation & storage
Intelligent search strategy selection
Semantic search & relevance ranking
Context-aware AI response creation
Create a new user account
Send a message to M-Maze
Retrieve conversation history
"Hi, my name is Alex and I'm a software developer."
"Nice to meet you, Alex! I'll remember that you're a software developer. What kind of projects do you work on?"
"What do you remember about me?"
"I remember that you're Alex, a software developer. We discussed your work on web applications and your interest in AI technologies."
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Full-stack development: From ideation to deployment, covering backend API, frontend interface, AI integration, and comprehensive documentation.