PersonaGen Documentation

Generate statistically-grounded synthetic personas for AI testing, user research simulation, and product development.

What is PersonaGen?

PersonaGen is an API that generates realistic synthetic personas with 77 demographic, psychological, and behavioral dimensions. Each persona is a coherent statistical combination — not a random collection of attributes.

The problem it solves: When you ask an LLM to “imagine a user,” you get the same profile every time — educated, urban, tech-savvy, moderate. Real populations are far more varied. PersonaGen restores that variety with statistically-grounded generation.

Core Principles

• Hierarchical dependencies — Education influences occupation, which influences income. Geography shapes career access. PersonaGen models these real-world correlations.
• Country-specific realism — US and UK personas use distinct value vocabularies, statistical distributions, and cultural frameworks.
• Deterministic seeds — Same seed, same persona. Every time.
• Sub-20ms generation — Fast enough for real-time workflows.

Quick Start

API Endpoints

Use Cases

• LLM grounding — Give language models diverse, realistic user contexts
• Journey mapping — Simulate how different demographics navigate your product
• Message testing — See how copy lands across varied audiences
• UX simulation — Walk user flows through demographically varied personas
• Research tooling — Generate test populations for surveys and studies

Response Structure

Every persona includes:

More Resources

• Dashboard Guide — Managing API keys and usage
• Roadmap & Limitations — What’s coming and current constraints