| What it does | Semantic context layer that helps AI agents understand your business data accurately
| Self-hosted multi-agent simulation framework for building autonomous agent civilizations
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| Stage | MVP
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| Developer License: $49 USD (one-time) includes Python/FastAPI engine source code, Vite/React observer dashboard, zero-cost mock mode, and single-user research grant. Commercial License: $149 USD (one-time) includes everything in Developer License plus perpetual royalty-free commercial distribution,
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| Key features | - Connects to 15+ data systems including Snowflake, Databricks, BigQuery, Redshift, dbt, Airflow, Tableau, Looker, Power BI and Postgres
- Extracts structural metadata including databases, schemas, tables, views, columns and relationship lineage
- Provides Web-UI, MCP server and REST APIs for accessing semantic context
- Automatic incremental updates with configurable sync schedules from on-demand to daily or weekly
- Role-level access controls and data classifications including PII, PHI and SPII
- Only reads metadata without accessing or moving actual data from systems
- Integrates with quality monitoring tools including Monte Carlo, Anomalo and Bigeye
| - Decoupled tick loop with independent tick rate scheduling
- SQLite WAL-mode persistence with concurrent reads and zero lock overhead
- Multi-generational genealogy and asset transaction logs
- Zero-token mock mode for local simulation without API costs
- Python/FastAPI backend with Vite/React observer dashboard
- Circadian cycles and natural mortality mechanics
- Seamless LLM integration with OpenAI, Anthropic, or Ollama
- Docker Compose deployment stack for Commercial License
- Instant source code delivery with digital license key
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| What makes it different | - Eliminates confident AI mistakes by grounding agents in semantic context instead of having them guess from table names
- Reduces AI token costs and speeds up answers by resolving schema and joins once upstream instead of in each agent query
- Ensures consistent answers across all agents and teams using the same definitions and business logic
- Provides complete traceability and auditability of AI decisions with documented context and ownership
| - Turnkey engineering for complex simulations without building the loop from scratch
- Zero recurring platform subscriptions with direct software licensing
- No lock overhead persistence with WAL-mode SQLite for concurrent reads
- Local LLM execution without incurring API costs in mock mode
- Royalty-free commercial distribution rights with Commercial License
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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) | 9 ▲ +1 (up) since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 1 | 0 |
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| Citation Flow (Majestic) | 24 | 0 |
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| Referring domains (Majestic) | 29 | 0 |
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Kanlet
Morgul Engine