# AIDC_2026

## AI Data Center Interactive Discovery

AIDC_2026 should function as an **interactive technology ownership map**, not merely a directory.

The supplied document already provides a strong initial taxonomy covering consumer hardware, infrastructure, communications, finance, entertainment, commerce, government, healthcare, and enterprise systems.  The service layer extends that structure into internet infrastructure, communication platforms, financial systems, entertainment, retail, government, healthcare, and industrial operations. 

The central investigative path becomes:

> **What am I using? → What technology powers it? → Which brand provides it? → Which corporation owns the brand? → Which data-center systems support it?**

## 1. Recommended application structure

```text
AIDC_2026
│
├── Consumer Devices
│   ├── Phones & Mobile Devices
│   │   ├── Smartphones
│   │   ├── Tablets
│   │   ├── Smartwatches
│   │   ├── E-readers
│   │   ├── Mobile payment terminals
│   │   └── GPS navigation devices
│   │
│   ├── Home Electronics
│   ├── Computers
│   ├── Gaming Hardware
│   ├── Vehicles
│   └── Networking Equipment
│
├── Data-Center Services
│   ├── Internet Infrastructure
│   ├── Communications
│   ├── Financial Systems
│   ├── Entertainment
│   ├── Retail & Commerce
│   ├── Government & Infrastructure
│   ├── Healthcare
│   └── Industrial & Enterprise
│
├── Technologies
│   ├── Cloud computing
│   ├── Content delivery networks
│   ├── AI inference
│   ├── Authentication
│   ├── Payments
│   ├── Telemetry
│   ├── Location services
│   ├── Streaming
│   └── Data storage
│
├── Brands
│
├── Corporations
│
├── Data-Center Operators
│
└── Ownership & Influence Explorer
```

## 2. Interaction model

Each level should reveal additional intelligence without forcing the user away from the page.

### Main category tooltip

**Phones & Mobile Devices**

> Portable connected devices that depend on data centers for authentication, cloud storage, application delivery, messaging, payments, synchronization, location services, software updates, advertising, analytics, and AI processing.

### Endpoint tooltip

**Smartphones**

> Connected handheld computers using cellular and Wi-Fi networks to communicate with cloud platforms, application stores, identity providers, payment systems, advertising networks, mapping services, media platforms, and AI services.

### Expanded endpoint panel

Clicking **Smartphones** could open a larger intelligence panel:

```text
DEVICE TYPE
Smartphone

COMMON BRANDS
Apple iPhone
Samsung Galaxy
Google Pixel
Motorola
OnePlus
Xiaomi
Huawei

PRIMARY TECHNOLOGIES
5G / LTE
Wi-Fi
Bluetooth
GPS
Cloud synchronization
Application distribution
Mobile payments
Biometric authentication
AI inference
Push notifications

DATA-CENTER DEPENDENCIES
Identity services
Cloud storage
Application stores
Messaging infrastructure
Advertising exchanges
CDNs
Streaming systems
Location databases
Payment processing
Telemetry collection

CORPORATE CONNECTIONS
Apple → iPhone, iOS, iCloud, App Store
Alphabet → Pixel, Android, Google Play, Maps
Samsung Electronics → Galaxy, SmartThings
Lenovo → Motorola Mobility
BBK-related brands → historical and structural links among several mobile brands
```

This makes the tooltip the doorway, while the detail panel becomes the evidence chamber.

## 3. The core data model

A simple category table will not be enough. The application needs a **relationship database**.

SQLite is ideal for the first standalone release. The PHP data layer can later support MySQL without redesigning the application.

### Primary entities

```sql
CREATE TABLE categories (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    parent_id INTEGER,
    name TEXT NOT NULL,
    slug TEXT NOT NULL UNIQUE,
    summary TEXT,
    tooltip TEXT,
    sort_order INTEGER DEFAULT 0,
    FOREIGN KEY (parent_id) REFERENCES categories(id)
);

CREATE TABLE endpoints (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    category_id INTEGER NOT NULL,
    name TEXT NOT NULL,
    slug TEXT NOT NULL UNIQUE,
    summary TEXT,
    tooltip TEXT,
    technical_description TEXT,
    data_center_dependency TEXT,
    FOREIGN KEY (category_id) REFERENCES categories(id)
);

CREATE TABLE companies (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    parent_company_id INTEGER,
    name TEXT NOT NULL,
    legal_name TEXT,
    ticker_symbol TEXT,
    headquarters TEXT,
    website TEXT,
    company_type TEXT,
    description TEXT,
    influence_summary TEXT,
    revenue_notes TEXT,
    market_position TEXT,
    confidence_score REAL,
    FOREIGN KEY (parent_company_id) REFERENCES companies(id)
);

CREATE TABLE brands (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    company_id INTEGER,
    name TEXT NOT NULL,
    website TEXT,
    description TEXT,
    ownership_notes TEXT,
    FOREIGN KEY (company_id) REFERENCES companies(id)
);

CREATE TABLE technologies (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    name TEXT NOT NULL,
    technology_type TEXT,
    description TEXT,
    data_center_role TEXT,
    ownership_notes TEXT
);

CREATE TABLE services (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    name TEXT NOT NULL,
    service_type TEXT,
    description TEXT,
    data_center_role TEXT
);

CREATE TABLE data_center_operators (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    company_id INTEGER,
    name TEXT NOT NULL,
    operator_type TEXT,
    regions TEXT,
    services TEXT,
    description TEXT,
    FOREIGN KEY (company_id) REFERENCES companies(id)
);
```

### Relationship tables

```sql
CREATE TABLE endpoint_brands (
    endpoint_id INTEGER NOT NULL,
    brand_id INTEGER NOT NULL,
    relationship_type TEXT,
    market_share REAL,
    notes TEXT,
    PRIMARY KEY (endpoint_id, brand_id)
);

CREATE TABLE endpoint_technologies (
    endpoint_id INTEGER NOT NULL,
    technology_id INTEGER NOT NULL,
    dependency_level TEXT,
    notes TEXT,
    PRIMARY KEY (endpoint_id, technology_id)
);

CREATE TABLE endpoint_services (
    endpoint_id INTEGER NOT NULL,
    service_id INTEGER NOT NULL,
    dependency_level TEXT,
    notes TEXT,
    PRIMARY KEY (endpoint_id, service_id)
);

CREATE TABLE company_technologies (
    company_id INTEGER NOT NULL,
    technology_id INTEGER NOT NULL,
    relationship_type TEXT,
    ownership_percentage REAL,
    notes TEXT,
    PRIMARY KEY (company_id, technology_id)
);

CREATE TABLE brand_technologies (
    brand_id INTEGER NOT NULL,
    technology_id INTEGER NOT NULL,
    relationship_type TEXT,
    notes TEXT,
    PRIMARY KEY (brand_id, technology_id)
);

CREATE TABLE service_operators (
    service_id INTEGER NOT NULL,
    operator_id INTEGER NOT NULL,
    relationship_type TEXT,
    notes TEXT,
    PRIMARY KEY (service_id, operator_id)
);
```

## 4. Ownership must be time-aware

Corporate ownership changes. A brand may be acquired, spun off, licensed, partially owned, or operated differently by region.

Instead of storing only:

```text
Motorola → Lenovo
```

store a historical relationship:

```sql
CREATE TABLE ownership_history (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    owner_company_id INTEGER NOT NULL,
    owned_entity_type TEXT NOT NULL,
    owned_entity_id INTEGER NOT NULL,
    ownership_type TEXT,
    ownership_percentage REAL,
    effective_date TEXT,
    end_date TEXT,
    source_url TEXT,
    source_name TEXT,
    verification_date TEXT,
    confidence_score REAL,
    notes TEXT
);
```

This allows AIDC_2026 to distinguish:

* Parent company
* Subsidiary
* Majority ownership
* Minority investment
* Joint venture
* Licensed brand
* Former ownership
* Regional ownership
* Technology partnership
* Infrastructure customer

That distinction is essential. Otherwise the corporate map becomes a bowl of ownership spaghetti.

## 5. Data correlation

The application should answer queries such as:

```text
Which corporations appear in the most categories?

Which brands depend on Amazon Web Services?

Which consumer devices connect to Alphabet-owned services?

Which companies own both hardware and cloud infrastructure?

Which corporations control the device, operating system,
application store, advertising network, and cloud service?

Which endpoints depend on a small number of infrastructure providers?

Which company has the greatest cross-category influence?

Which brands have changed ownership?

Which technologies are controlled by competitors but used together?
```

### Example correlation path

```text
Smartphone
   ↓
Google Pixel
   ↓
Google LLC
   ↓
Alphabet Inc.
   ↓
Android
Google Play
Google Cloud
Google Maps
Firebase
YouTube
Google Ads
   ↓
Device software
Application distribution
Location services
Cloud hosting
Media delivery
Telemetry
Advertising
AI processing
```

The user can begin with a familiar object and descend into the corporate machinery beneath it.

## 6. Corporate influence scoring

“Corporate influence” should not be presented as one unsupported number. It should be calculated from visible components.

```text
Corporate Influence Score
├── Endpoint coverage
├── Category coverage
├── Brand ownership
├── Technology ownership
├── Infrastructure ownership
├── Estimated market share
├── Revenue contribution
├── Consumer confidence
├── Geographic reach
├── Data dependency
└── Supply-chain concentration
```

A preliminary formula could be:

```text
Influence Score =
    Endpoint Coverage × 15%
  + Category Coverage × 10%
  + Market Share × 20%
  + Infrastructure Control × 20%
  + Technology Ownership × 15%
  + Revenue Position × 10%
  + Consumer Confidence × 10%
```

Every score should show its sources, calculation date, methodology, and confidence level.

## 7. Source and verification system

Market share, ownership, revenue, and consumer-confidence information will need supporting evidence.

```sql
CREATE TABLE sources (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    title TEXT NOT NULL,
    publisher TEXT,
    source_url TEXT,
    publication_date TEXT,
    accessed_date TEXT,
    source_type TEXT,
    reliability_rating INTEGER,
    notes TEXT
);

CREATE TABLE evidence_links (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    entity_type TEXT NOT NULL,
    entity_id INTEGER NOT NULL,
    field_name TEXT,
    source_id INTEGER NOT NULL,
    quoted_value TEXT,
    verification_status TEXT,
    FOREIGN KEY (source_id) REFERENCES sources(id)
);
```

Suggested verification states:

```text
Verified
Probable
Estimated
Disputed
Historical
Unverified
Needs Review
```

## 8. Interface aesthetic

The OSINT/AI atmosphere should feel analytical rather than costume-hacker neon.

### Visual language

```text
Background:       #06090d
Panels:           #0b1118
Raised panels:    #101923
Primary text:     #d8e2e8
Muted text:       #71828f
Signal green:     #52ff9a
Intelligence cyan:#42d9ff
Warning amber:    #ffbd4a
Critical red:     #ff4d62
Borders:          #21313d
```

### Interface regions

```text
┌──────────────────────────────────────────────────────────────┐
│ AIDC_2026   AI DATA CENTER INTERACTIVE DISCOVERY            │
│ Search [____________________]  Dataset Status: ACTIVE        │
├──────────────────┬───────────────────────────────────────────┤
│ CATEGORY TREE    │ INTERACTIVE DISCOVERY MAP                 │
│                  │                                           │
│ Consumer Devices │  Phones & Mobile Devices                  │
│ Services         │      ├─ Smartphones                       │
│ Technologies     │      ├─ Tablets                           │
│ Corporations     │      ├─ Smartwatches                      │
│ Infrastructure   │      └─ GPS Navigation                    │
│                  │                                           │
├──────────────────┴───────────────────────────────────────────┤
│ SELECTED ENDPOINT INTELLIGENCE                               │
│ Ownership | Technology | Infrastructure | Market | Sources   │
├──────────────────────────────────────────────────────────────┤
│ CORPORATE CORRELATION MATRIX                                 │
└──────────────────────────────────────────────────────────────┘
```

Useful visual elements:

* Expandable category tree
* Hover tooltips
* Click-to-pin intelligence cards
* Relationship lines between entities
* Corporate ownership badges
* Confidence indicators
* Source counters
* Dependency severity markers
* Search by device, brand, company, or technology
* “Trace ownership” mode
* “Trace infrastructure” mode
* “Compare corporations” mode
* Correlation matrix
* JSON export
* CSV export
* Printable intelligence report

## 9. Recommended technical stack

```text
Backend
PHP 8.1+
PDO database abstraction
SQLite for standalone deployment
Optional MySQL configuration

Frontend
Semantic HTML5
Vanilla JavaScript
CSS custom properties
SVG relationship lines
No framework required initially

Database
/data/aidc.sqlite

Configuration
/config/config.php

Data exchange
JSON API endpoints

Optional later additions
D3.js for network visualization
Chart.js for market-share charts
Leaflet for geographic infrastructure
```

## 10. Proposed project layout

```text
AIDC_2026/
├── index.php
├── endpoint.php
├── company.php
├── brand.php
├── technology.php
├── search.php
│
├── api/
│   ├── categories.php
│   ├── endpoints.php
│   ├── endpoint-details.php
│   ├── companies.php
│   ├── ownership.php
│   ├── relationships.php
│   └── search.php
│
├── admin/
│   ├── index.php
│   ├── categories.php
│   ├── endpoints.php
│   ├── companies.php
│   ├── brands.php
│   ├── technologies.php
│   ├── relationships.php
│   └── sources.php
│
├── assets/
│   ├── css/
│   │   ├── base.css
│   │   ├── interface.css
│   │   ├── tooltips.css
│   │   └── visualization.css
│   ├── js/
│   │   ├── app.js
│   │   ├── discovery.js
│   │   ├── tooltip.js
│   │   ├── search.js
│   │   └── correlations.js
│   └── img/
│
├── config/
│   └── config.php
│
├── data/
│   ├── aidc.sqlite
│   └── seed.sql
│
├── includes/
│   ├── database.php
│   ├── functions.php
│   ├── header.php
│   └── footer.php
│
└── schema/
    ├── sqlite.sql
    └── mysql.sql
```

## 11. First development phase

The most sensible first build is:

1. Import the complete supplied category and endpoint structure.
2. Build the expandable discovery tree.
3. Add category and endpoint tooltips.
4. Add detailed endpoint panels.
5. Create companies, brands, and technology records.
6. Connect endpoints to brands and parent corporations.
7. Display a corporate directory at the bottom.
8. Add search and ownership tracing.
9. Add source citations and confidence values.
10. Add market-share and influence calculations after the structural data is stable.

The resulting first version would already let a user click:

```text
Consumer Devices
→ Phones & Mobile Devices
→ Smartphones
→ Apple iPhone
→ Apple Inc.
→ iOS / App Store / iCloud
→ Data-center services
→ Infrastructure dependencies
```

That is the correct foundation for AIDC_2026: an interactive **device-to-data-center-to-corporation intelligence graph** wrapped in a standalone PHP application.