Slaunt 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.
Slaunt compared with Perseus Computing
| Detail |
Slaunt |
Perseus Computing |
| What it does | The all-in-one agentic AI solution for your organization
| High-assurance infrastructure for AI agents
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| Stage | Startup
| Not given
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| Founded | 2024
| Not given
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| Based in | Not given
| US
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| Pricing model | Freemium
| Open source
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| Pricing | Starter (free), Professional ($29/seat/month), Enterprise (contact for pricing)
| Not given
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| Key features | - Centralized context repository for unifying work signals across tools
- MCP protocol integration with AI assistants and tools
- First-class integrations with GitHub, Vercel, Supabase, Railway, Gmail, Notion, Calendly, Codex, Claude Code, and Slack
- Per-agent scoped access with full audit trail
- Custom vector embeddings for agent memory
- Instant agent shutdown from anywhere globally
- QUAERO enterprise AI agent governance system
- Two-way sync with tools for agent actions and work flows
- Support for custom MCP servers and internal tools
- Real-time organizational context for agent reasoning
| - 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 | - AI-first design with structured, queryable context rather than static documentation
- Consistent policy and audit rules across all integrations
- MCP-native integrations with no bespoke connectors to maintain
- Instant global agent shutdown capability
- Guardrails on every agent run by default
| - 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
| Not given
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| Community votes | 0 | 0 |
| DR (Domain Rating by Ahrefs) | 4 ● no change since last check | 42 ▲ +1 (up) since last check |
| Trust Flow (Majestic) | 0 | 3 |
| Citation Flow (Majestic) | 28 | 24 |
| Referring domains (Majestic) | 40 | 62 |
4 details filled in for both companies.
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