| What it does | Local-first orchestration layer that converts natural language goals into validated plans, policy checks, and real tool execution
| AI agent orchestration platform that models workflow with triggers, actors, stages, gates, permissions, and outcomes
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| Stage | Startup
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| Founded | 2025
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| Based in | Not given
| US
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| Pricing model | Not given
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| Pricing | Free: $0 with single local runtime, core tool registry, session memory, demo mode. Intelligence: $49/month with multi-agent delegation, Visual Workflow Studio, Security Center, MCP protocol, 7 LLM providers, native desktop app. Enterprise: custom pricing with distributed agent mesh, security policy
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| Key features | - Visual Workflow Studio with drag-and-drop pipeline canvas
- Natural language chain generation from plain English descriptions
- Step-by-step debugger with real-time node animation
- Policy gates and human approval for destructive operations
- Multi-agent delegation with consensus workflows
- AES-256-GCM encrypted secrets vault
- Support for 7 LLM providers including Ollama
- Immutable SOC 2-style audit log with SHA-256 hash chains
| - Role-based organization with humans or AI agents in any position
- Workflow definitions with triggers, stages, gates, and outcomes
- Agent-agnostic design supporting Claude, Codex, Gemini, and local models
- Scoped credentials with least privilege access per stage
- Deterministic gates for tests, reviews, and approvals
- Audit trail with hash-chained tamper-evident ledger
- Local-first deployment with optional cloud hosting
- Isolated git worktrees for independent work and verification
- Budget tracking and spend monitoring per organization
- Separation of duties enforced in code
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| What makes it different | - Fully local execution with no cloud infrastructure dependency required
- Human-in-the-loop approval system for governance and risk mitigation
- Native desktop application with bundled runtime and zero prerequisites
- Visual pipeline design without code required
| - Orchestration layer that treats work as executable processes rather than remembered habits or wikis
- Roles swappable between humans and AI agents without rewriting workflows
- Credentials and secrets held by infrastructure, never exposed to AI models
- Autonomous AI decision-making within defined stages, deterministic controls at stage boundaries
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 26 ▲ +1 (up) since last check | 24 ▲ +1 (up) since last check |
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| Trust Flow (Majestic) | 1 | 7 |
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| Citation Flow (Majestic) | 23 | 31 |
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| Referring domains (Majestic) | 63 | 18 |
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MachinaOS
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