| What it does | Keep the why with your code
| Synthetic test data generator for PostgreSQL that reads your live schema and generates realistic data without production data
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| Stage | Not given
| Startup
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| Founded | Not given
| 2025
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| Based in | Not given
| SK
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| Pricing model | Open source
| Freemium
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| Pricing | Not given
| Free plan: $5 of monthly credits ($10 with work email), around 8 seeding runs per month on a 30-table schema. Basic plan: $16/month with $32 of monthly credits (2x payment), around 50 runs per month. Premium plan: $69/month with $180 of monthly credits (2.6x payment), around 300 runs per month, prio
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| Key features | - Records stated reasoning for changes the agent logs
- Entity-level attribution for code elements
- Retrieves recorded attempts and outcomes
- Groups related changes across files
- Full-text search over change history
- Exports to Agent Trace format
- Local SQLite storage with no hosted backend
- MCP and CLI interfaces
- Concurrent readers and writers with WAL mode
| - Reads live database schema to generate coherent test data automatically
- Generates realistic data at scale from hundreds to tens of millions of rows
- Maintains foreign key integrity and constraint satisfaction
- Generates localized data with culturally appropriate names and formats
- Works as CLI, MCP server for AI editors, and CI/CD pipeline step
- Handles complex schemas with composite keys and multi-level dependencies
- Plan preview shows exactly what will be seeded before writing any rows
- Never requires access to production databases
- Generates data with realistic distributions across columns and tables
- Most runs complete in under three minutes
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| What makes it different | - Zero network dependencies; all storage and history queries run locally
- Captures reasoning at the time of change from the agent's own context
- MIT-licensed open source with no vendor lock-in
- Works with any compatible AI agent through standard MCP protocol
- Validates reasoning quality to surface low-quality logs
| - No production data exposure: generates all test data from schema alone, eliminating privacy and compliance risks
- Schema-aware generation creates coherent, relational data without manual seed scripts
- Integrated with AI editors through MCP server for seamless developer workflow
- Realistic data that surfaces real bugs, not random placeholder values
- Works at any scale with consistent data integrity from dozens to tens of millions of rows
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 36 ● no change since last check | 8 ▼ −19 (down) since last check |
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| Trust Flow (Majestic) | 5 | 27 |
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| Citation Flow (Majestic) | 31 | 32 |
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| Referring domains (Majestic) | 97 | 62 |
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