MiroFish vs Taurus
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
MiroFish compared with Taurus
| Detail | M
MiroFish | 
Taurus |
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| What it does | A simple and universal swarm intelligence engine
| Lead armies of AI agents sanely
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| Stage | Not given
| Not given
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| Founded | 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 | Starter: $7.50/month (monthly) or $9/month (annual); Pro: $15.83/month (monthly) or $19/month (annual); Premium: $40.83/month (monthly) or $49/month (annual). Annual plans save 17%.
| 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 | - Upload PDF, Markdown, and text documents to seed simulations
- Convert source material into ontology and graph structure
- Run parallel simulations with up to 1 million agents per run
- Generate prediction reports with key risks and confidence signals
- Deep interaction through ReportAgent or direct character interviews
- Dual-surface simulation across Twitter and Reddit style channels
- Follow-up questions in the same workspace for continued analysis
- Build executable scenarios for public opinion, market, policy, and narrative use cases
| - 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 | - Inspectable AI forecasts treated as exploratory hypotheses before operational decisions
- Review simulations before upload with the Forecast Explorer gallery
- Graph-native simulation that exposes actor incentives, narrative spread, and reaction chains
- Templates and guides for recurring scenario types like crises and product launches
- Keeps judgment with humans on scenario boundaries and high-stakes operating calls
| - 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) | 56 ● no change since last check | 31 ● no change since last check |
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| Trust Flow (Majestic) | 5 | 0 |
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| Citation Flow (Majestic) | 30 | 30 |
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| Referring domains (Majestic) | 160 | 115 |
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5 details filled in for both companies.
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