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Comparison

A factual comparison of approaches to deploying AI agents in production.

KruxOS vs raw Docker

Feature KruxOS Docker container
Agent interface 89 typed capabilities via MCP-native (JSON-RPC fallback) Shell commands, text parsing
Error handling Structured errors with typed codes, recovery suggestions Exit codes, stderr text
Permission control 4-tier policy engine with rate limits Unix permissions (root or not)
Audit trail Hash-chained append-only logs, queryable Container logs (deletable, unstructured)
Secret management Encrypted vault, use-not-read model Environment variables (visible to agent)
Multi-agent isolation Per-agent namespaces, cgroups, seccomp, nftables (Landlock adds in v0.0.3) Per-container isolation
External service safety Read-replica, write buffer, batch protection, rollback Direct API access
Agent-to-agent comms Built-in message broker with policy integration Custom implementation needed
Human oversight Approval queue, real-time dashboard, live activity stream Manual log inspection
State management 3-tier persistence (session/persistent/shared) Filesystem or external database
Tool discovery Auto-discovery with schemas and documentation Custom documentation
Updates A/B partition with automatic rollback Container image replacement
Setup time 5 min (Docker) / 15 min (VM image) Varies (custom Dockerfile)
Token efficiency ~60% fewer tokens (structured responses) Baseline

When to use Docker instead: If you need complete control over the runtime environment, are running agents that don't interact with the OS, or have existing container infrastructure that you want to reuse.

When to use KruxOS: If you need governance, audit trails, human oversight, multi-agent support, or safe external service access.

KruxOS vs OpenClaw

Feature KruxOS OpenClaw
Skill/capability model Typed YAML definitions with semantic types JSON definitions with loose types
Permission model 4-tier deterministic policy engine All-or-nothing
Audit trail Hash-chained, append-only, tamper-detectable None
Secret management Encrypted vault, capability-scoped, use-not-read Environment variables
Sandbox isolation 4-layer kernel isolation in v0.0.1 (ns + cgroup v2 + seccomp + nftables); Landlock adds 5th layer in v0.0.3 None
External service safety Read-replica + write buffer + batch protection + rollback Direct API access
Error handling Structured errors with recovery suggestions Unstructured text
Multi-agent Session isolation, comms, shared state Single agent
Human oversight Dashboard, approval queue, CLI supervision None
Community skills 13,000+ via compatibility bridge 13,000+ native
Migration effort Automatic importer with type inference N/A
Model support Claude (MCP native), OpenAI, Gemini, Ollama, any local Varies
OS integration Purpose-built Linux distribution Application layer

Migration path: KruxOS includes an OpenClaw compatibility bridge that lets existing OpenClaw agents connect without code changes. Skills can be gradually migrated to native capabilities for full type safety and governance.

KruxOS vs NemoClaw

Feature KruxOS NemoClaw
Architecture Purpose-built OS with kernel-level isolation Application framework on existing OS
Governance Deterministic YAML policy engine Configuration-based restrictions
Audit Hash-chained append-only logs with tamper detection Application-level logging
Sandbox Linux kernel mechanisms (4 layers in v0.0.1, 5 in v0.0.3) Application-level sandboxing
Vault Dedicated encrypted vault with use-not-read Credential store
Service Proxy Read-replica + write buffer + batch protection Direct API access
Open source Apache 2.0 (community edition) Proprietary
Model support Any model (MCP native for Claude, adapters for others) NVIDIA ecosystem focused
Community OpenClaw-compatible, 13,000+ importable skills NVIDIA ecosystem

Feature matrix

Feature KruxOS Docker OpenClaw NemoClaw
Typed API capabilities Yes No Partial Partial
Deterministic policy engine Yes No No Partial
Hash-chained audit Yes No No No
Encrypted secret vault Yes No No Partial
Kernel-level sandboxing Yes Partial No No
Service Proxy (read-replica) Yes No No No
Write buffer + cancellation Yes No No No
Batch protection Yes No No No
Human approval workflow Yes No No Partial
Real-time dashboard Yes No No Yes
Multi-agent comms Yes No No Partial
A/B update with rollback Yes No No No
Model-agnostic Yes Yes Yes Partial
Community skill ecosystem 13K+ (via bridge) N/A 13K+ NVIDIA
Open source Yes Yes Yes No

Cost comparison

Approach Infrastructure Licensing Agent token cost
KruxOS (community) 1 server / VM Free (Apache 2.0) ~40% lower than Docker
KruxOS (enterprise) 1+ servers Commercial license ~40% lower than Docker
Docker 1+ servers Free Baseline
OpenClaw 1+ servers Free Similar to Docker
NemoClaw NVIDIA hardware Commercial license Varies

The ~40% token cost reduction comes from structured responses eliminating the output parsing and error guessing that consume tokens on unstructured platforms.