--profile saas
Bias generated values toward a B2B SaaS product: workplace emails, startup-style company names, plan-tier enums, and dates clustered in the last 18 months.
- startup and company names mixing single-word brands with "X-ly" and "Get-X" patterns
- workplace email addresses (alice@acme.com), not gmail / hotmail / personal domains
- plausible SaaS job titles (Engineer, PM, Designer, Head of Ops)
- billing-plan and feature-flag enums when the column name suggests them (free, pro, team)
- dates clustered in the last 18 months; subscriptions distributed across plans
| column | example |
|---|---|
| orgs.name | Northbeam Analytics |
| users.email | alice@northbeam.io |
| users.title | Staff Engineer |
| subscriptions.plan | pro |
| users.created_at | 2025-11-04T09:22:11Z |
Profiles bias value choice; they don’t define your schema. The table set, column types, and FK graph come from introspecting your own database. Rows are validated against your Postgres constraints before they land.
--profile ecommerce
Bias generated values toward a consumer e-commerce store: realistic product names across apparel/home/accessories, prices with familiar retail cents, and orders skewed toward fulfilled.
- product names across apparel, home goods, and accessories
- prices between 9.99 and 299.99 with cents ending in .99 / .49 / .00
- customer names and shipping addresses drawn from US / UK / DE / FR / JP
- order statuses biased toward fulfilled, with a long tail of pending and refunded
| column | example |
|---|---|
| products.title | Cedar Plank Cutting Board, 18" |
| products.price | $34.99 |
| customers.country | DE |
| orders.status | fulfilled |
| orders.total | $84.50 |
Profiles bias value choice; they don’t define your schema. The table set, column types, and FK graph come from introspecting your own database. Rows are validated against your Postgres constraints before they land.
--profile b2b
Bias generated values toward a B2B service or marketplace: mid-market accounts, contract values, multi-seat licensing, and procurement-style metadata. Consumer language is avoided.
- mid-market company names with a named-account feel
- contract values in the $5,000 to $250,000 range
- multi-seat licensing (seat counts, per-seat unit prices)
- procurement metadata: PO numbers, NET-30 terms, MSA dates
- no consumer language (no shopping, no household products)
| column | example |
|---|---|
| accounts.name | Meridian Freight Systems, Inc. |
| contracts.value_usd | $78,000 |
| contracts.seats | 45 |
| contracts.payment_terms | NET-30 |
| contracts.po_number | PO-2026-01849 |
Profiles bias value choice; they don’t define your schema. The table set, column types, and FK graph come from introspecting your own database. Rows are validated against your Postgres constraints before they land.
no profile? no problem.
Omit --profile and the CLI runs with a neutral system prompt. Values still respect column types, nullability, unique constraints, check constraints, and foreign keys—you just don’t get the domain-flavored biases. Useful for internal schemas that don’t map cleanly onto SaaS, e-commerce, or B2B.
More profiles (legal, real estate, logistics, healthcare) are on the roadmap and will be pinned by user demand. Open an issue with your CREATE TABLE statements and a short description of the domain and we’ll triage.