Architecture

Understanding Mamentis architecture is key to leveraging its full potential. Our platform is built on a model-agnostic foundation that prioritizes flexibility, performance, and scalability.

System Overview

Mamentis operates on a three-tier architecture:

┌─────────────────────────────────────────────────────────┐
│                   User Interface Layer                  │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐     │
│  │ Chat Screen │  │ Core Screen │  │  Partners   │     │
│  └─────────────┘  └─────────────┘  └─────────────┘     │
└─────────────────────────────────────────────────────────┘
                              │
┌─────────────────────────────────────────────────────────┐
│                Intelligence Routing Layer               │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐     │
│  │ Task Router │  │ Model Mgmt  │  │ Performance │     │
│  └─────────────┘  └─────────────┘  └─────────────┘     │
└─────────────────────────────────────────────────────────┘
                              │
┌─────────────────────────────────────────────────────────┐
│                   Model Integration Layer               │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐     │
│  │   OpenAI    │  │  Anthropic  │  │   Google    │     │
│  │   Models    │  │   Models    │  │   Models    │     │
│  └─────────────┘  └─────────────┘  └─────────────┘     │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐     │
│  │    Meta     │  │   Mistral   │  │   Custom    │     │
│  │   Models    │  │   Models    │  │   Models    │     │
│  └─────────────┘  └─────────────┘  └─────────────┘     │
└─────────────────────────────────────────────────────────┘

Core Components

1. Intelligence Routing Layer

The heart of Mamentis is our intelligent routing system that:

• Analyzes incoming tasks to understand requirements
• Evaluates available models based on performance metrics
• Routes requests to the optimal model for the task
• Learns from results to improve future routing decisions

2. Model Integration Layer

Our abstraction layer that:

• Normalizes APIs across different model providers
• Handles authentication and rate limiting
• Manages failover between models
• Monitors performance and availability

3. User Interface Layer

The frontend that provides:

• Unified chat interface for natural language interactions
• Core management tools for models, data, and settings
• Partner integration for collaborative workflows
• Activity monitoring and analytics

Key Architectural Principles

Model Agnostic Design

Mamentis doesn't favor any particular AI model or provider. Instead, we've built an abstraction layer that can work with any API-compatible model, allowing us to:

• Add new models quickly as they become available
• Compare performance across different providers
• Provide redundancy and failover capabilities
• Give users choice in their AI toolchain

Task-Specific Optimization

Our routing intelligence considers multiple factors when selecting models:

• Task type (text generation, code, analysis, etc.)
• Response time requirements
• Quality benchmarks for specific use cases
• Cost optimization based on user preferences
• Model availability and current load

Scalable Infrastructure

Built on cloud-native principles:

• Microservices architecture for independent scaling
• Container orchestration for efficient resource usage
• Auto-scaling based on demand
• Geographic distribution for low latency

Data Flow

1. User Input: Query or task submitted through interface
2. Task Analysis: System analyzes requirements and context
3. Model Selection: Routing layer selects optimal model
4. Processing: Request sent to chosen model with optimized parameters
5. Response Handling: Result processed and formatted for user
6. Learning: Performance data captured for future improvements

This architecture ensures that you always get the best possible results while maintaining the flexibility to adapt as new models and capabilities become available.

Next: Learn how to Set Up Mamentis for your specific needs.