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Monolithos vs Taurus

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

Monolithos compared with Taurus
Detail MonolithosTaurus logo Taurus
What it doesPersonal Agent OS built from memory you own Lead armies of AI agents sanely
StageNot given Not given
FoundedNot given Not given
Based inNot given Not given
Pricing modelFreemium Freemium
PricingNot 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
Key features
  • User-owned memory in Markdown and YAML
  • Eight modules: Memory, Flow, Black Hole, Minutes, Codex, Prism, Audio, Facet
  • Multi-step AI tasks with human approval checkpoints
  • Meeting transcription sealed into memory
  • Markdown-to-presentation generation with Prism
  • Audio generation from notes
  • Visual asset library with provenance tracking
  • Private domain boundaries to exclude content from cloud AI
  • Project mode to bind files and conversations into sealed context
  • Compatible with existing Obsidian vaults without migration
  • 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
  • Memory and data remain on your device and under your ownership, never used for model training
  • Files stay readable as plain Markdown and YAML with any text editor; no vendor lock-in possible
  • Works with existing Obsidian vaults natively without import or conversion
  • Private-domain content stays out of cloud AI context automatically
  • AI recall includes sources so you can see what answers are based on
  • 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 votes00
DR (Domain Rating by Ahrefs)3 no change since last check31 no change since last check
Trust Flow (Majestic)90
Citation Flow (Majestic)2130
Referring domains (Majestic)22115

4 details filled in for both companies.

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