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Swiss AI Hub

Part I: Vision & Positioning

Introduction: The Swiss AI Hub Vision

The Problem We Solve

Our solution

The Swiss Way

Platform vs SDK

Why Swiss AI Hub

Comparison Matrix

The 'Day 2' Advantage

The Ecosystem Model

Full Competitor Analysis

Core Components

The Infrastructure Layers

Part II: The Platform Journey

Quick Start: Your First 30 Minutes

Prerequisites

One-Command Deployment

First Login

Your First Conversation

Your First Insights

What Just Happened?

Platform Architecture

System Context

Containers

Swiss AI Agent Protocol

Docker Network Isolation

Package-Centered Views

Deployment Guide

Deployment Options

Production Configuration

Scaling Considerations

Backup and Recovery

Monitoring & Alerting

External Log Aggregation

Updates & Maintenance

Network requirements

Web search

Environment Variables

Identity Provider Setup

Microsoft Entra ID

Azure App Registration

User and Role Management

User Interface

Agents

Agent fundamentals

Blueprints & Profiles

Instructed Assistant

Teachable Assistant

Document Intelligence Assistant

Retrieval Agent

Document Navigation Assistant

MCP Tool Agent

Expert Coordinator Agent

Company Knowledge Agent

Data pipelines

Fundamentals

RAG ingestion pipeline

Agentic Processes

Knowledge management

Organizing knowledge with collections

Agent evaluations

Chat Interface

Feature overview

Chat Messages

Chat with your Data

Chat with your company knowledge

Web search capability

Coding / Software Development

Screen Sharing

Voice Input

User feedback

Observability

Integration architecture

Strategic rationale

Access Management

Authentication Setup

Permission and Access Control

Auditing & Observability

High-Level Interactions

Low-Level Traces

Language models

Proxy server

Data anonymization

Input/output guards

Cost control

Memory

User Memory

Organization Memory

Multi-tenancy

How multi-tenancy works

Setting up tenants

Managing users and roles

Technical reference - Access control

IDP-based tenant assignment

Slack & Teams Integrations

Azure Bot Service Integration

Bot Creation Manual Setup Guide

API

OpenAI-Compatible REST API

Agent Interaction REST API

WebSocket API

Dynamic Agent and Process Endpoints

API Tokens

Model Context Protocol (MCP)

Security

Authentication and Authorization

Input Validation

Container Security

Network security

Data Encryption

Compliance and regulations

Data Retention Policies

GDPR Compliance

Swiss Data Protection Act (DSG)

EU AI Act

Internationalization

Data Subject Access Requests (DSAR)

External system integrations

Part III: The SDK Journey

Quick Start

Development Environment Setup

SDK Architecture

Your First Agent

Your First Pipeline

Why our SDK

Building Agents

Agent Fundamentals

Core Workflow Patterns

Human in the loop

Multi-Agent Systems

Agent Memory

Testing and debugging

Production Deployment

Agent Observation

Configurable Agent Forms

Execution Model

Events Reference

Using MCP Tools

Building Pipelines

Pipeline Fundamentals

Core Patterns

Data Ingestion Pipeline

Job Scheduling

Pipeline Observation

Building Processes

Process Fundamentals

Delegation Patterns

External Process Tools

Testing Processes

Production Deployment

Production Observation

Advanced SDK Topics

Custom Semantic Events

State Management

Performance Optimizations

Error Handling

Extensibility and Customization

Features

Bot-in-the-Loop

Part IV: The Ecosystem Journey

Contributing

Contribution Guidelines

Arch42 Decision Records

Testing Requirements

Documentation Standards

Pull-Request Process

Using AI to Contribute

Core Terminology

MCP Servers

Vibe Coding Guidelines

Certification

Certification Path

SDK Licensing

Commercial Licensing

Support and Training

Part V: Reference & Resources

API Reference

REST & Sockets API

Event Reference

SDK Reference

Config Reference