| What it does | The control layer for AI
| The model training platform for AI teams
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| Stage | Not given
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| Founded | Not given
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| Based in | Not given
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| Pricing model | Freemium
| Freemium
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| Pricing | Free plan: €0/month with 10,000 proofs included per month. Starter: €59/month with 50,000 proofs, then €0.0015 per proof above. Growth: €249/month with 500,000 proofs, then €0.0005 per proof, then €0.0002 after 2,000,000 proofs. Enterprise: from €990/month or €15,000/year licence with 5,000,000 proo
| Free: $0/month with $50 in credits once, 1 seat per project, every feature, console, CLI and MCP server, community Discord support. Pro: $120/month with $120 in credits every month, unlimited seats, priority support. Enterprise: Custom pricing, contact for details.
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| Key features | - Wraps AI provider clients with policy enforcement before calls execute
- Enforces provider-level privacy parameters like store=false for OpenAI
- Generates signed, non-reusable ACT tokens for each request
- Maintains append-only, hash-chained ledger for audit verification
- Embedded preference widget with cross-app persistence
- Global Privacy Control signal detection and enforcement
- Fails closed when unreachable; no fallback mode
- Python and Node.js SDKs with source-available licence
- Policies defined in dashboard, not in code
| - OpenTelemetry agent tracing and trace import from Langfuse, LangSmith, Braintrust and Galileo
- Generated evals and Agent Optimizer runs that return scored code diffs
- Data Workshop with dataset preparation and quality checks
- Model training with recommended settings for LoRA or full fine-tuning
- Benchmarks against your current model on the same eval set
- Hosted OpenAI-compatible inference and downloadable model weights
- Console, CLI and MCP server access
- OpenAI-compatible API for trained models
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| What makes it different | - Cryptographic proof of compliance: signed, verifiable tokens and append-only ledger that auditors can verify without vendor involvement
- Policies live in dashboard, never touch code, preventing unauthorized modifications
- Separates user preference control from developer code, ensuring developer cannot alter consent
| - Own your trained models with downloadable weights and checkpoints
- Zero third-party training with data never leaving your pipeline
- Open source and self-hostable with Docker Compose
- Built by security and defense intelligence pioneers
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | 44 ● no change since last check |
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| Trust Flow (Majestic) | 0 | 10 |
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| Citation Flow (Majestic) | 0 | 35 |
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| Referring domains (Majestic) | 0 | 201 |
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ID side
Overmind