| What it does | The confidential agentic stack for defense, finance, and regulated teams
| Semantic context layer that helps AI agents understand your business data accurately
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| Stage | Not given
| MVP
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| Founded | Not given
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| Based in | US
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| Pricing model | Freemium
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| Pricing | Pay as you go: from $20 prepaid credits, provider cost plus 10% markup, $25 increments. Team: $1,200/seat/year (5-seat minimum). Enterprise Sovereign: $2,400/seat/year. Sovereign Government: custom pricing. Blackbit add-on: $4,999/named operator/month (2-operator minimum).
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| Key features | - Confidential AI IDE (CDE) for secure coding assistance with protected repositories and terminals
- Confidential LLM Gateway with access to hundreds of models through governed interface
- Hardware-protected sandboxed environments for code and agent execution
- Cryptographic attestation and audit trails for workload verification
- Agents SDK for private agent execution with controlled tool access
- Support for private, restricted, and air-gapped deployments
- Trusted Execution Environment (TEE) models on sovereign infrastructure
- SSO and RBAC for enterprise access control
- Blackbit autonomous security agent for agentic cyber tasks
| - 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
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| What makes it different | - Hardware-backed isolation and attestation replacing traditional policy-based security
- Zero-retention model ensuring code stays within protected environments
- Verifiable execution with audit trails for compliance and security verification
- Flexible deployment from self-serve credits to sovereign air-gapped environments
| - 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
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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) | 28 ● no change since last check | 8 ● no change since last check |
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| Trust Flow (Majestic) | 19 | 1 |
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| Citation Flow (Majestic) | 32 | 24 |
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| Referring domains (Majestic) | 300 | 29 |
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Orgn
Kanlet