# NGIE-AI Current Platform Architecture

**Snapshot date:** July 6, 2026  
**Detailed reference:** `docs/NGIE_AI_ARCHITECTURE_OVERVIEW.md`

## What NGIE-AI Is Today

NGIE-AI is now a deterministic Business Knowledge Operating System that can ingest ecosystem websites, convert them into structured knowledge, build relationships, generate business intelligence, make rule-based recommendations, and produce client-ready ecosystem assessments without using AI APIs yet.

```text
Websites
   ↓
Extraction Pipeline
   ↓
Knowledge Objects
   ↓
Search + Review + Explorer
   ↓
Knowledge Graph
   ↓
Business Intelligence
   ↓
Decision Engine
   ↓
Ecosystem Assessment
   ↓
Future Client Products
```

The current implementation includes an Industry Solutions bridge between the Decision Engine and Ecosystem Assessment.

## Folder Flow

```text
sources/
   ↓
knowledge/
   ↓
knowledge/objects/
   ↓
knowledge/relationships/     (logical; relationships currently live in objects)
   ↓
knowledge/graph/
   ↓
reports/
   ↓
reports/client-assessments/
```

## Current Platform Summary

| Area | Current status |
| --- | --- |
| Website pages processed | 137 across 6 websites |
| Metadata files | 137 |
| Canonical knowledge objects | 137 |
| Review | 29 approved; 100 pending; 3 needs revision; 5 rejected |
| Review warnings | 0 unresolved thin objects; 0 active duplicates |
| Graph | 859 nodes; 2,958 edges; 1 component; no orphans or dangling edges |
| Business Intelligence | 21.2% approved; 6 organizations; not ready for AI reasoning |
| Decision Engine | 6 deterministic business profiles |
| Industry Solutions | 6 blueprints; deployment disabled |
| Ecosystem Assessment | Operational and tested; JSON, Markdown, PDF placeholder |
| Workflow Engine | 3 deterministic workflows; allow-list, dry-run, fail-fast, and audit records |
| Sample assessment | 39/100; 17 approved supporting objects |
| ChatGPT preparation | Ready, but no official export is present |

## Component Status

| # | Component | Main input | Main output | Status |
| ---: | --- | --- | --- | --- |
| 1 | Website Source Registry | `sources/websites.yaml` | Active source definitions | Complete |
| 2 | Website Knowledge Extraction | Registry and websites | `knowledge/<site>/{raw,cleaned,pages,metadata,reports}` | Operational |
| 3 | ChatGPT Export Preparation | Future `conversations.json` | Private import folders and readiness check | Prepared; awaiting export |
| 4 | Website Knowledge Object Generator | Page Markdown and metadata | `knowledge/objects/*.json` | Operational; 137 objects |
| 5 | Local Knowledge Search | Canonical objects | Ranked local results and optional index | Operational |
| 6 | Knowledge Review Workflow | Canonical objects | Review fields and status reports | Operational |
| 7 | Knowledge Explorer | Objects and ID map | Interactive terminal exploration | Operational |
| 8 | Knowledge Graph | Objects and relationships | Graph JSON/JSONL and metrics | Operational |
| 9 | Business Intelligence | Objects and graph | `intelligence/*` and BI report | Operational; gated |
| 10 | Decision Engine | Objects, graph, and BI | Six business profiles | Operational |
| 11 | Ecosystem Assessment | Client input and all downstream platform layers | Client assessment JSON, Markdown, and PDF | Operational and tested |
| 12 | Workflow Engine | Workflow registry and local platform dependencies | Audited workflow runs and step logs | Operational and tested |

## Component Connections

1. The registry selects active sources.
2. The crawler turns websites into raw HTML, cleaned HTML, Markdown, and metadata.
3. The object generator normalizes extracted pages into the canonical schema.
4. Search, review, and the Explorer expose and govern canonical objects.
5. The graph materializes object relationships.
6. BI summarizes quality, coverage, organizations, and graph signals.
7. The Decision Engine creates organization profiles and rule-based candidates.
8. Industry Solutions package approved evidence into industry blueprints.
9. The Ecosystem Assessment combines declared client inputs with approved evidence and produces client-facing artifacts.
10. The Workflow Engine makes refresh, validation, and assessment execution reproducible without adding autonomous behavior.

## Architecture Observations Requiring Validation

- `knowledge/objects/` contains 137 canonical objects.
- `knowledge/classification-index.json` and the persisted search index contain 322 derived documents. These must remain clearly separated from canonical counts.
- There is no physical `knowledge/relationships/` directory. Relationship fields are stored in objects and graph edges.
- Website caps left 1,061 discovered URLs queued or deferred.
- Only 29 canonical objects are approved, so BI correctly reports that the repository is not ready for AI reasoning.
- Assessment recommendations are evidence-linked and deterministic, but the PDF is still a placeholder.
- The official private ChatGPT export has not been imported.

## Recommended Next Build

1. Architecture validation report.
2. Test assessment using one sample business.
3. Assessment report template improvements.
4. Simple local dashboard.
5. AI reasoning layer after validation.

This report documents current state only. It does not introduce new runtime features.