Documentation

Getting Started with DataEcho

Learn how to generate realistic, semantic-aware test data for your applications.

Overview

DataEcho is an enterprise-grade synthetic data generation platform that uses a multi-agent AI pipeline to create realistic, relationship-aware test data. It supports traditional databases, AI/RAG applications, and agentic AI systems.

Quick Start

Get started in under 5 minutes:

  1. Sign in — Use your credentials to access the dashboard
  2. Create a project — Click "New Project" and choose your input mode
  3. Upload data or describe — Upload sample files or describe your requirements
  4. Configure & generate — Set extrapolation, row counts, and export format
  5. Download results — Review quality report and export your data

API Authentication

All API requests require a Bearer token in the Authorization header.

bash
curl -H "Authorization: Bearer YOUR_API_KEY" \
  https://api.dataecho.cloud/v1/projects

Create a Project via API

json
POST /v1/projects
{
  "name": "E-commerce Test Data",
  "mode": "prompt",
  "prompt": "Generate 10K users, 50K orders, 5K products",
  "config": {
    "extrapolation": true,
    "expansion_factor": 5,
    "model": "gemini-3.1-flash-lite",
    "use_case": "standard"
  }
}

Features

Extrapolation Mode

Expand data variety beyond input. Turn 4 categories into 50+ realistic variations.

Relationship Mapping

Auto-detect and preserve foreign key relationships across datasets.

RAG Data Generation

Generate Q&A pairs, query variations, and adversarial inputs for RAG testing.

Agent Scenario Generation

Create multi-turn conversations and tool-call sequences.