withHuman vs Taurus
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
withHuman compared with Taurus
| Detail | 
withHuman | 
Taurus |
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| What it does | The approval layer for AI agents
| Lead armies of AI agents sanely
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| Stage | Not given
| Not given
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| Founded | Not given
| Not given
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| Based in | US
| Not given
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| Pricing model | Freemium
| Freemium
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| Pricing | Open Source: free and self-hosted. Free: $0/month hosted plan with up to 5 members. Scale: $20 per user per month. Enterprise: Custom annual contract.
| Free: $0 with 10 agents, 2 parallel runs, 2 GB storage. Start: $20/month with 100 agents, 5 parallel runs, 10 GB storage. Plus: $50/month with 300 agents, 12 parallel runs, 50 GB storage. Pro: $200/month with 1000 agents, 30 parallel runs, 250 GB storage. On paid plans, model usage billed at true pr
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| Key features | - Tool call interception for all agent frameworks
- Automatic approval rules to prevent fatigue
- AI judge for complex rule evaluation
- Works with LangGraph, CrewAI, Mastra, Claude Agent SDK and more
- Open Agent Approval Protocol for framework independence
- Self-hosted or cloud-hosted deployment options
- Custom permission policies and organization controls
| - Hierarchical agent trees with parent-child delegation and coordination
- Container-isolated agent environments with Linux shell and persistent filesystem
- Persistent agent memory and context between runs
- Cron-based scheduled execution with overlap handling
- Shared /shared folder for cross-agent file collaboration
- Support for 30+ AI models from multiple providers
- Web IDE with terminal access and five editor themes
- Static site dashboards built and maintained by agents
- Voice input and file attachment support
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| What makes it different | - Framework-agnostic: works with any AI agent through the open Agent Approval Protocol
- No vendor lock-in: open source spec and SDKs let you swap providers without rewriting agents
- Comprehensive audit trail for accountability and compliance
- Meets reviewers where they work with multi-platform notifications
- Policy-based routing to eliminate approval bottlenecks
| - Agentic tree structure where agents collaborate and share context unlike stateless tools
- Fully isolated Linux containers for each agent with persistent filesystems
- Persistent memory and context continuity across scheduled runs
- Mix and match 30+ AI models freely within the same team
- Pricing per fleet rather than per seat or per token overage
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 30 ▼ −1 (down) since last check | 31 ● no change since last check |
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| Trust Flow (Majestic) | 6 | 0 |
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| Citation Flow (Majestic) | 28 | 30 |
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| Referring domains (Majestic) | 48 | 115 |
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5 details filled in for both companies.
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