Moonborn.
Moonborn — Plans

Which planfits you?

Plans are organized around how you use Moonborn: exploration, individual production, team collaboration, or enterprise rollout.

Free

For exploring Moonborn and building your first characters.

  • Single-user workspace
  • Character generation with Soul → Self → Mask → Surface
  • Basic consistency checks
  • Persona export support
  • Community support
Start for free
Pro

For solo builders, indie developers, writers, and freelancers shipping real projects.

  • Larger persona library and higher usage limits
  • Voice fingerprinting and stress tests
  • Lineage management for character variants
  • OpenAI-compatible endpoint, MCP, and SDK support
  • Email support
Talk to us
Team

For teams collaborating on characters, brand voices, research panels, or AI products.

  • Multi-user workspaces
  • Role-based access control
  • Shared persona library
  • Webhook and audit log support
  • Priority support
Talk to us
Enterprise

For larger rollouts, regulated environments, security reviews, and custom requirements.

  • SSO, SCIM, and custom role management
  • Region selection and enterprise data policies
  • Extended audit log and retention options
  • Custom agreements, DPA, and security reviews
  • SLA-backed customer support
Contact sales

How usage-based cost is estimated

Production cost depends on volume, model choice, context length, test frequency, and active consistency checks. For high-volume workloads, we help estimate monthly cost before rollout.

What affects usage cost?

LLM calls, test runs, embeddings, context length, and cache hit rates all affect total cost. The main cost drivers become visible before production rollout.

Generating one persona
Depends on the selected models and active pipeline steps.
One chat response
Depends on the model, context length, memory policy, and consistency checks.
Running one stress test
Depends on the number of tests, judge model, retries, and failure policy.
Building a voice fingerprint
Depends on the number of scenarios, generated samples, and embedding model.

Compare the full feature matrix