| What it does | Open-sourcing Karotte, a framework for building robust reinforcement learning environments
| 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 | - Sandboxed execution with non-privileged user isolation
- Process termination before grading
- Suspicious file detection and rejection
- Out-of-memory and fork-bomb prevention
- Hardened through one million evaluation runs
- Red-team tested for reward hacking vulnerabilities
- Scalable environment execution
- Robust benchmark building support
| - 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 | - Provides secure defaults and primitives specifically designed to prevent reward hacking in RL training
- Hardened through real-world testing at scale with over one million evaluation runs
- Designed for training environments where defenses must withstand continuous optimization attempts
- Addresses AI alignment at the highest leverage point through better environment construction
- Built and tested internally by frontier AI research team
| - 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) | 29 ▲ +1 (up) since last check | 8 ▼ −19 (down) since last check |
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| Trust Flow (Majestic) | 11 | 27 |
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| Citation Flow (Majestic) | 24 | 32 |
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| Referring domains (Majestic) | 98 | 62 |
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Preference Model