Privaro vs Perseus Computing
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Privaro compared with Perseus Computing
| Detail | 
Privaro | 
Perseus Computing |
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| What it does | AI governance and privacy platform that detects PII, masks prompts and audits LLM traffic
| High-assurance infrastructure for AI agents
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| Stage | Not given
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| Founded | Not given
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| Based in | ES
| US
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| Pricing model | Paid
| Open source
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| Pricing | Starter: €150/month or €120/month (annual). Growth: €250/month. Business: €400/month or €320/month (annual). Scale: €700/month. Enterprise: €1,250/month. Enterprise+: €2,500/month. Volume-based pricing available for >5M requests/month. 14-day free trial available. Additional requests: €15 per extra
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| Key features | - Multi-provider LLM routing for OpenAI, Anthropic, Mistral, Groq, and OpenAI-compatible endpoints
- Immutable blockchain-certified audit logs via iCommunity Blockchain Services
- Governance dashboard with visibility into AI usage, policy enforcement, and audit logs
- Privacy-first governed chat interface for enterprise teams
- Output scanning to detect and anonymize sensitive data in model responses
- Context optimization reducing token usage by up to 57% on logs and tool outputs
- Exportable DPO reports in PDF for compliance documentation
- RAG protection with Privaro Ingest and Retrieval Guard with per-chunk access control
| - Harpe: chooses what an AI agent reads under a token budget with consistent results
- Kibisis: keeps agent memory on your hardware with AES-256-GCM encryption
- Argus: append-only record that detects edits with cryptographic verification
- No network code by default for local and disconnected use
- MIT License with published code, benchmarks and raw results
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| What makes it different | - Blockchain-certified immutable audit trail provides legally admissible evidence for compliance and regulatory audits
- Works with any LLM provider through unified multi-provider routing without vendor lock-in
- Reduces LLM costs through context optimization that compresses logs and outputs before model inference
- Built specifically for regulated industries with pre-configured use cases for legal, healthcare, and fintech
- No integration friction with endpoint-level proxy requiring only an endpoint change in LLM calls
| - Measured empirical validation across 6,111 questions outperforming full-context models
- Zero plaintext on disk with encrypted vaults matching plaintext accuracy
- 78.3% fewer tokens sent to the model with a 1,200-token budget per turn
- Preserves conversational chronology and relational qualifiers under token budgets
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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) | 8 ▼ −1 (down) since last check | 42 ▲ +1 (up) since last check |
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| Trust Flow (Majestic) | 11 | 3 |
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| Citation Flow (Majestic) | 15 | 24 |
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| Referring domains (Majestic) | 50 | 62 |
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5 details filled in for both companies.
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