Phony Cloud Platform

"Realistic data. Zero risk."
Phony is the next-generation synthetic data platform combining open-source developer tools with enterprise-grade cloud services.

Quick Start

Get up and running with Phony in under 5 minutes.

Step 1: Install the CLI

bash

# macOS / Linux
curl -fsSL https://phony.cloud/install.sh | sh

# Windows (PowerShell)
irm https://phony.cloud/install.ps1 | iex

# Verify installation
phony --version

Step 2: Train Your First Model

Create a file with sample names (one per line):

bash

# Create sample data
cat > names.txt << 'EOF'
Mehmet
Ayşe
Fatma
Ahmet
Zeynep
Mustafa
Elif
Ali
Hatice
Hüseyin
EOF

# Train the model
phony train names.txt -o names.phony

# Inspect the model
phony info names.phony

Output:

Model: names.phony
├── Locale: auto-detected
├── N-gram order: 3
├── Token type: character
├── Unique tokens: 18
├── Total n-grams: 45
└── Created: 2026-01-31T10:00:00Z

Step 3: Generate Data (PHP)

bash

# Install PHP library
composer require phonycloud/phony-php

php

<?php
use Phonyland\Phony\Phony;

// Load your custom model
$names = Phony::loadModel('names.phony');

// Generate 10 Turkish-sounding names
for ($i = 0; $i < 10; $i++) {
    echo $names->generate() . "\n";
}

// Output:
// Mehmetay
// Zeyneli
// Fatmah
// Ayset
// Huseyina

Step 4: Use with Laravel (Optional)

bash

composer require phonycloud/phony-laravel

php

// In a Factory
use Phonyland\Phony\Facades\Phony;

public function definition(): array
{
    return [
        'first_name' => Phony::name()->first(),
        'last_name' => Phony::name()->last(),
        'email' => Phony::email()->generate(),
        'created_at' => now(),
    ];
}

// In a Seeder
User::factory()->count(1000)->create();

Next Steps

Goal	Resource
Understand generator types	Architecture → Generator Types
Learn PDL schema language	Architecture → PDL Specification
Explore CLI commands	Reference → CLI
Connect to Cloud	Product → Overview

The Vision

Phony is the next-generation synthetic data platform that combines open-source developer tools with enterprise-grade cloud services. Unlike competitors that rely on expensive LLMs or static word lists, Phony uses statistical learning to generate data that's indistinguishable from real data—fast, cheap, and private.

┌─────────────────────────────────────────────────────────────────────────┐
│                          PHONY ECOSYSTEM                                │
│                                                                         │
│                         ┌─────────────┐                                 │
│                         │   PHONY     │                                 │
│                         │   CORE      │                                 │
│                         │             │                                 │
│                         │  N-gram     │                                 │
│                         │  Statistical│                                 │
│                         │  Engine     │                                 │
│                         └──────┬──────┘                                 │
│                                │                                        │
│                    ┌───────────┴───────────┐                            │
│                    ▼                       ▼                            │
│        ┌───────────────────┐   ┌───────────────────────┐               │
│        │   PHONY           │   │   PHONY CLOUD         │               │
│        │   Open Source     │   │   phony.cloud         │               │
│        │                   │   │                       │               │
│        │   • CLI & Library │   │   • Web Dashboard     │               │
│        │   • Local Training│   │   • DB Column Training│               │
│        │   • Any Language  │   │   • Database Sync     │               │
│        │   • Any Framework │   │   • Mock API Hosting  │               │
│        │   • Free Forever  │   │   • Team Features     │               │
│        └───────────────────┘   └───────────────────────┘               │
│                                                                         │
│        For: Individual devs    For: Teams & Companies                   │
│        Cost: Free              Cost: $29-199/mo                         │
└─────────────────────────────────────────────────────────────────────────┘

The Problem

Production Data in Non-Production Environments

Companies copy production databases to staging, development, and QA environments—exposing real customer data to breaches and compliance violations.

Unrealistic Test Data

Traditional fake data tools generate generic, predictable output that doesn't match real data distributions.

Faker output:        Your real data:
─────────────        ──────────────
"John Smith"         "Mehmetcan Yılmaz"
"123 Main St"        "Atatürk Mah. 15/3"
"Lorem ipsum..."     Domain-specific text

Tests pass with fake data but fail with real data.

Existing Solutions Fall Short

Solution	Limitation
Faker	Static lists, no learning, generic
Tonic Structural	Expensive ($199+/mo), enterprise-only
Tonic Fabricate	LLM-based = slow, costly, non-deterministic
Greenmask	PostgreSQL only, no mock API

The Opportunity

Market	Current (2026)	Projected (2031)	CAGR
Synthetic Data	~$700M	$8-10B	35%+
Test Automation	$30B	$100B+	17%

Gap in market: No solution combines statistical learning + mock API + Laravel-first design.

Key Numbers

Metric	Target
Exit ARR	$600K-1M
Exit Multiple	5-8x ARR
Exit Value	$3-8M (realistic)
Customers at Exit	300-500
Timeline	4-5 years

Pricing Overview

★ ALL TIERS: UNLIMITED GENERATION + UNLIMITED USERS ★

Tier	Price	Sync Jobs	Endpoints	Snapshots
FREE	$0	1	5	3
STARTER	$29/mo	5	30	10
TEAM	$79/mo	15	150	50
BUSINESS	$199/mo	Unlimited	Unlimited	Unlimited

Why unlimited generation? Our N-gram engine costs ~$0.0000001/record vs LLM's $0.001-$0.10/record.

OSS vs Cloud

Feature	OSS (Free)	Cloud (Paid)
Pre-trained models	✓	✓
Local model training	✓	✓
Model portability (.phony)	✓	✓
DB column training	✗	✓
Database sync	✗	✓
Data snapshots	✗	✓
Mock API hosting	✗	✓
Team collaboration	✗	✓

Tech Stack

┌────────────────┐   ┌────────────────┐   ┌────────────────┐
│     NUXT       │   │       GO       │   │      RUST      │
│   Dashboard    │ → │    Engine      │ → │     Core       │
├────────────────┤   ├────────────────┤   ├────────────────┤
│ Vue 3 + TS     │   │ pgx (Postgres) │   │ N-gram (5M/s)  │
│ Auth.js        │   │ go-mysql       │   │ gzipped JSON   │
│ Stripe SDK     │   │ asynq (queue)  │   │ FFI to Go      │
└────────────────┘   └────────────────┘   └────────────────┘

PDL Architecture

Phony introduces PDL (Phony Definition Language) - a declarative, portable schema for data generation.

┌─────────────────────────────────────────────────────────────────────────┐
│                    "TERRAFORM FOR TEST DATA"                             │
├─────────────────────────────────────────────────────────────────────────┤
│                                                                          │
│  PDL Schema                    .phony Package                            │
│  (schema.pdl.json)     →       (portable bundle)                        │
│                                       │                                  │
│                        ┌──────────────┼──────────────┐                   │
│                        ▼              ▼              ▼                   │
│                    ┌──────┐      ┌──────┐      ┌──────┐                 │
│                    │ CLI  │      │ OSS  │      │Cloud │                 │
│                    │(Rust)│      │Libs  │      │(Rust)│                 │
│                    └──────┘      └──────┘      └──────┘                 │
│                    Training      10-50K/s      5M/sec                    │
│                                                                          │
│  SAME PACKAGE → SAME OUTPUT (deterministic with seed)                   │
│                                                                          │
└─────────────────────────────────────────────────────────────────────────┘

4 Generator Types:

Type	Purpose	Example
Logic	Pure algorithms	UUIDs, random numbers, dates
List	Finite valid sets	Countries, HTTP codes, categories
Model	Statistical (N-gram)	Names, addresses, companies
Template	Composition	Email, full address, formatted output

📚 Learn more: Architecture Overview

Phony Cloud Platform ​

Quick Start ​

Step 1: Install the CLI ​

Step 2: Train Your First Model ​

Step 3: Generate Data (PHP) ​

Step 4: Use with Laravel (Optional) ​

Next Steps ​

The Vision ​

The Problem ​

Production Data in Non-Production Environments ​

Unrealistic Test Data ​

Existing Solutions Fall Short ​

The Opportunity ​

Key Numbers ​

Pricing Overview ​

OSS vs Cloud ​

Tech Stack ​

PDL Architecture ​

Phony Cloud Platform

Quick Start

Step 1: Install the CLI

Step 2: Train Your First Model

Step 3: Generate Data (PHP)

Step 4: Use with Laravel (Optional)

Next Steps

The Vision

The Problem

Production Data in Non-Production Environments

Unrealistic Test Data

Existing Solutions Fall Short

The Opportunity

Key Numbers

Pricing Overview

OSS vs Cloud

Tech Stack

PDL Architecture