ATLAS 2.0 Documentation

Complete platform specification for the next-generation agentic business planning system.

Core Philosophy

"A business plan is not a document. It's a living strategy that adapts, learns, and executes."

ATLAS 2.0 represents a paradigm shift in business planning technology. While existing solutions focus on document creation, ATLAS 2.0 is designed as an Autonomous Business Intelligence System that doesn't just help you write a plan—it actively builds your business alongside you.

What Makes ATLAS Different

• Agentic Architecture: Six specialized AI agents work autonomously on research, analysis, and generation
• Conversational Interface: Build your entire plan through natural dialogue—no forms or templates
• Real-time Intelligence: Continuous market research, competitor monitoring, and regulatory tracking
• Predictive Simulation: Monte Carlo modeling to forecast business outcomes before you invest
• Post-Plan Continuity: Seamless transition from planning to execution with Launch Sequence

Quick Start

Get your first business plan started in under 5 minutes:

1. Create Account: Sign up at atlas-platform.io (free tier available)
2. Start Conversation: Click "New Project" and describe your business idea
3. Let Agents Work: ATLAS dispatches research agents while you continue the conversation
4. Review & Refine: Access the Intelligence Dashboard to see findings and adjust
5. Generate Documents: Export your plan in any format when ready

System Architecture

ATLAS 2.0 is built on a Multi-Agent Orchestration Framework where specialized AI agents work autonomously while a central Conductor coordinates their efforts.

┌─────────────────────────────────────────────────────────────────────┐
│                         USER INTERFACE LAYER                        │
│  ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐  │
│  │   Web    │ │  Mobile  │ │  Voice   │ │   AR/VR  │ │   API    │  │
│  └────┬─────┘ └────┬─────┘ └────┬─────┘ └────┬─────┘ └────┬─────┘  │
└───────┼────────────┼────────────┼────────────┼────────────┼────────┘
        └────────────┴────────────┼────────────┴────────────┘
                                  ▼
┌─────────────────────────────────────────────────────────────────────┐
│                      ORCHESTRATION LAYER                            │
│  ┌────────────────────────────────────────────────────────────┐    │
│  │                    CONDUCTOR AGENT                          │    │
│  │   • Goal Decomposition    • Agent Coordination              │    │
│  │   • Resource Allocation   • Human-in-Loop Triggers          │    │
│  └────────────────────────────────────────────────────────────┘    │
└───────────────────────────────┬─────────────────────────────────────┘
                                ▼
┌─────────────────────────────────────────────────────────────────────┐
│                     SPECIALIST AGENT SWARM                          │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐                 │
│  │  RESEARCH   │  │  FINANCIAL  │  │  STRATEGY   │                 │
│  │   AGENT     │  │   AGENT     │  │   AGENT     │                 │
│  └─────────────┘  └─────────────┘  └─────────────┘                 │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐                 │
│  │  DOCUMENT   │  │   CONNECT   │  │ OPERATIONS  │                 │
│  │   AGENT     │  │   AGENT     │  │   AGENT     │                 │
│  └─────────────┘  └─────────────┘  └─────────────┘                 │
└───────────────────────────────┬─────────────────────────────────────┘
                                ▼
┌─────────────────────────────────────────────────────────────────────┐
│                    INTELLIGENCE LAYER                               │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐              │
│  │   MEMORY     │  │   KNOWLEDGE  │  │   LEARNING   │              │
│  │   SYSTEM     │  │    GRAPH     │  │   ENGINE     │              │
│  └──────────────┘  └──────────────┘  └──────────────┘              │
└───────────────────────────────┬─────────────────────────────────────┘
                                ▼
┌─────────────────────────────────────────────────────────────────────┐
│                      DATA LAYER                                     │
│  ┌───────────┐ ┌───────────┐ ┌───────────┐ ┌───────────┐           │
│  │PostgreSQL │ │  Vector   │ │  Redis    │ │    S3     │           │
│  │  + JSONB  │ │   Store   │ │   Cache   │ │  Storage  │           │
│  └───────────┘ └───────────┘ └───────────┘ └───────────┘           │
└─────────────────────────────────────────────────────────────────────┘

The Agent Swarm

Six specialized agents operate in parallel, each with distinct capabilities:

Pillar 1: GENESIS — Idea Crystallization

The "10-Minute Business" experience starts with a conversation, not a form:

ATLAS: "Tell me about the business you're dreaming of. 
        Don't worry about structure—just share your vision."

USER:  "I want to open a cheesecake shop in a small town..."

ATLAS: "I love it. Let me understand more...
        
        → Who do you see as your ideal customer?
        → What makes your cheesecakes special?
        → Do you have a location in mind?
        
        Take your time—I'll listen and build while we talk."

Behind the Scenes

• Natural Language Understanding — Extracts entities, concepts, constraints
• Industry Classification — Maps to NAICS codes, identifies regulatory frameworks
• Initial Research Dispatch — Agents begin market research immediately
• Assumption Generation — Creates testable hypotheses about the business

The Oracle — Predictive Simulation

The Oracle runs Monte Carlo simulations across 10,000 scenarios to provide:

• Success Probability Score — Overall likelihood of achieving profitability
• Key Risk Factors — Specific variables that most affect outcomes
• Cash Flow Stress Testing — Identify when and why cash runs low
• Optimal Launch Timing — Best month/season to open based on data
• Failure Mode Analysis — Specific scenarios that lead to closure

ATLAS: "I've simulated 10,000 versions of your business 
        over the next 3 years. Here's what I found:
        
        📊 Success Probability: 72%
        
        Key Insights:
        → Cash is tightest in Month 4 (87% of failures happen here)
        → Summer seasonal boost is critical to your model
        → Adding delivery increases success rate to 81%
        
        Want to explore different scenarios?"

Technology Stack

Frontend

Backend

AI/ML Layer

API Reference

Core Endpoints

/api/v1:
  /projects:
    GET    - List user's projects
    POST   - Create new project
    /{id}:
      GET    - Get project details
      PUT    - Update project
      DELETE - Archive project
      
  /agents:
    POST   - Dispatch research request
    /{task_id}:
      GET    - Check task status
      DELETE - Cancel task
      
  /documents:
    GET    - List documents
    POST   - Generate document
    /{id}/export - Export to format
    
  /chat:
    POST   - Send message to ATLAS
    /history - Conversation history

Security Architecture