System Architecture

NAEOS is built on a layered architecture with five main layers:

┌─────────────────────────────────────────────────────────┐
│                      Input Layer                          │
│            Spec YAML/JSON · CLI Commands                  │
├─────────────────────────────────────────────────────────┤
│                      Core Runtime                         │
│   Parser · Normalizer · Resolver · Validator · Scheduler │
├─────────────────────────────────────────────────────────┤
│                    Reasoning Layer                         │
│            Reasoning Graph · Knowledge Graph               │
├─────────────────────────────────────────────────────────┤
│                    Generation Layer                        │
│   Generator · Adapters · Template Engine · Compiler       │
├─────────────────────────────────────────────────────────┤
│                      Output Layer                          │
│   NEIR Model · Code · Docs · AI Context · Manifests       │
└─────────────────────────────────────────────────────────┘

1. Input Layer

The entry point where specifications (YAML/JSON) and CLI commands enter the system.

2. Core Runtime

Handles parsing, normalization, cross-reference resolution, validation, and DAG-based scheduling.

3. Reasoning Layer

The decision-making layer with a reasoning graph for traceability and a knowledge graph for domain understanding.

4. Generation Layer

Multi-language code generation with per-language adapters and AI instruction compilation.

5. Output Layer

Produces the NEIR model, generated code, documentation, AI context bundles, and deployment manifests.

Design Principles

Human-readable specifications — YAML/JSON as the single source of truth
Machine-readable NEIR — Canonical intermediate representation for all downstream processing
Vendor neutral — Multi-language, multi-cloud, multi-AI-platform
Extensible — Adapters, plugins, and profiles for customization
Deterministic — Same input always produces the same output

Key Components

NEIR Model

The NAEOS Engineering Intermediate Representation describes the entire system: project, architecture, modules, services, APIs, storage, infrastructure, security, AI, documentation, deployment, testing, and metadata.

Pipeline Engine

A 9-stage DAG-based pipeline: Parse → Normalize → Resolve → Build → Validate → Schedule → Generate → Compile → Export.

AI Compiler

Transforms NEIR into AI instruction sets for 6 target platforms: GitHub Copilot, Claude Code, Cursor, Gemini CLI, Codex, and OpenCode.

Governance

Policy evaluation, RBAC, audit trails, and artifact review workflows.

Edit this page