Jev vs Taurus
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Jev compared with Taurus
| Detail | 
Jev | 
Taurus |
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| What it does | API access without the waitlist: one key, two endpoints
| Lead armies of AI agents sanely
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| Stage | Not given
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| Founded | Not given
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| Based in | 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 | - Custom criteria: POST state with choice options and score rubrics
- Eight pre-measured rulesets: support-ticket-triage, llm-model-routing, agent-tool-selection, content-moderation, phishing-detection, rag-reranking, agent-output-guardrails, lead-scoring
- Probability distributions over all choices and scores
- Parallel question evaluation within one call
- Key rotation and deletion
- TypeSafe key support for direct billing
| - 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 | - No waitlist: get a key immediately with email or Google sign-in
- Measured pricing: real calls cost ~20× less than vendor-circulated figures
- Input-only pricing with no output tokens
- Eight rulesets with published exact calls and measured output
- Transparent cost reporting with versioned model IDs in responses
| - 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) | 26 ▼ −1 (down) since last check | 31 ● no change since last check |
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| Trust Flow (Majestic) | 18 | 0 |
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| Citation Flow (Majestic) | 24 | 30 |
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| Referring domains (Majestic) | 80 | 115 |
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4 details filled in for both companies.
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