Built for data teams & developers

Stop hand-crafting fake data.
Generate it.

Synthloom produces millions of realistic, relationship-aware records in minutes — so your team can test, prototype, and demo with confidence. No coding required.

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1M+ Records in minutes
Zero Coding required
100% Referentially intact
AI Realistic enrichment
Core Capabilities

Everything you need to synthesize real-world data

Referential Integrity

Automatic foreign key management ensures every generated relationship is coherent. Customers, Orders, Products — all linked correctly, every time.

DAG-Based Dependency Resolution

A directed acyclic graph engine resolves entity ordering, detects circular dependencies, and unlocks parallel generation across independent layers.

Parallel Generation

Independent entity groups are generated concurrently, dramatically reducing wall-clock time for complex, multi-entity datasets.

AI Enrichment

Plug in OpenAI GPT or Anthropic Claude to generate context-aware descriptions, narratives, and realistic text fields — with result caching to control costs.

Multiple Output Formats

Export as CSV, JSON, Parquet, or write directly to a SQL database. Parquet output is optimized for big data pipelines; JSON supports per-entity split files.

Declarative YAML Rules — Zero Coding Required

Define entities, fields, constraints, and relationships in YAML. Rules are reusable, version-controllable, and shareable across teams.

Post-Generation Validation

Automated validators check foreign key constraints, uniqueness, value ranges, and custom business logic after every generation run.

Memory-Efficient Streaming

Batch-based streaming generation means no dataset is ever fully loaded into memory — enabling billion-record generation on commodity hardware.

How It Works

From data modeling to data files in six steps

01

Define Model

Declare your data model — entities, fields, types, and relationships — in YAML or via the visual Rule Editor.

02

Resolve Dependencies

The DAG engine topologically sorts entities and groups independent ones for parallel execution.

03

Stream Generate

Records are produced in memory-efficient batches. IDs are cached to satisfy foreign keys downstream.

04

AI Enrich

Optional LLM pass adds realistic copy, descriptions, and contextual text to marked fields.

05

Export

Write output as CSV, JSON, or Parquet — ready for any downstream pipeline or analytics tool.

06

Validate

Automated validators confirm referential integrity, uniqueness, and business-rule compliance.

Step-by-step tutorials

New to Synthloom? Start with the docs.

Detailed walkthroughs for every section of the app — from defining your first data model to validating million-row outputs.

Read the Documentation →

See Synthloom
in action

Get a personalised walkthrough of how Synthloom can accelerate your team's data generation workflows — from model definition to million-row exports.

  • Live demo of the visual Rule Editor & Pipeline view
  • Walk through AI enrichment & validation
  • Q&A tailored to your use case
  • 30 minutes — no commitment required

Who should we expect?

Calendar subject will read: Synthloom Demo: Your Name

Curious who's behind Synthloom?

Meet the Team →

Ready to generate?

Open the app and start synthesizing data in under a minute.

Open Synthloom →

Synthloom