runx vs Taurus
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
runx compared with Taurus
| Detail | 
runx | 
Taurus |
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| What it does | Give your agent specialist skills for the work around your product
| 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 | Not given
| Not given
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| Pricing model | Freemium
| Freemium
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| Pricing | Not given
| 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 | - Pre-built skills for business ops, organic growth, research and development
- Compose skills into repeatable workflows
- Signed receipts recording each run
- Run locally without account via open-source CLI
- Secure credential management through connectors
- Approval gates for spending and publishing actions
- Integration with Claude Code, Codex, Cursor and other agents
- Connect to GitHub, Slack, Apollo, Linear, Notion, Sentry and more
| - 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 | - Runs skills locally on your machine via open-source CLI without requiring an account
- Keeps credentials secure in connectors so they never appear in skills or receipts
- Records every action in a signed receipt for full audit trail
- Write and combine your own skills into custom workflows
| - 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) | 17 ▲ +1 (up) since last check | 31 ● no change since last check |
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| Trust Flow (Majestic) | 10 | 0 |
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| Citation Flow (Majestic) | 29 | 30 |
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| Referring domains (Majestic) | 68 | 115 |
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4 details filled in for both companies.
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