Cronloop vs Taurus

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Cronloop compared with Taurus
Detail	Cronloop	Taurus
What it does	AI agents that run on a schedule to automate recurring work	Lead armies of AI agents sanely
Stage	Not given	Not given
Founded	Not given	Not given
Based in	Not given	Not given
Pricing model	Not given	Freemium
Pricing	Free plan: $0 per month with up to 3 agents, runs as often as every hour, 200 run minutes each month, runs up to 10 minutes, 1 active run at a time. Pro plan: $25 per month ($20 per month when billed annually) with no fixed agent limit, runs as often as every 5 minutes, no fixed monthly run-minute l	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
Key features	Create agents with Markdown descriptions Run agents on custom schedules from every 5 minutes to once a week Agents keep memory and self-improve between runs Connect any tool with an API, MCP, or CLI Sandbox environment with package installation MCP server for ChatGPT and Claude integration Live output and run history Support for subscriptions and API keys	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
What makes it different	Agents remember previous runs and continuously self-improve Works with any tool, API, or skill via integrations Control agents directly from ChatGPT and Claude Fresh sandbox for each run with automatic package installation	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
Community votes	0	0
DR (Domain Rating by Ahrefs)	16 +1 (up) since last check	31 no change since last check
Trust Flow (Majestic)	5	0
Citation Flow (Majestic)	27	30
Referring domains (Majestic)	101	115

4 details filled in for both companies.

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