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How TriOnyx differs from OpenClaw

TriOnyx is a security-first reimagining of the OpenClaw agent runtime. Where OpenClaw sandboxes capability (restrict filesystem, disable shell, limit network), TriOnyx tracks information -- what enters an agent's context and where it flows next.

TriOnyx OpenClaw
Core focus Security-first agent runtime with information flow control Multi-platform AI assistant gateway
Security thesis Information is the threat, not capability -- track what agents have seen, not just what they can do Capability sandboxing -- restrict filesystem, shell, and network access per session
Primary language Elixir/OTP (+ Python, Go) TypeScript (+ Swift, Kotlin)
Gateway design Non-agentic OTP control plane -- no LLM, no autonomy, deterministic security boundary WebSocket control plane managing sessions, channels, tools, and events
Agent isolation Each agent in its own Docker container with per-agent FUSE filesystem, iptables rules, no shared state Docker sandboxing for non-main sessions; shared-state sessions via JSONL transcripts
Taint tracking Biba integrity model -- tracks exposure to untrusted content (prompt injections, web data) Not implemented
Sensitivity tracking Bell-LaPadula confidentiality -- tracks access to secrets, credentials, private data Not implemented
Information flow enforcement Gateway intercepts all inter-agent messages; blocks flows violating integrity or confidentiality constraints; graph analysis for transitive risk Not implemented at the information-flow level
Credential handling Gateway is sole credential holder -- agents never see raw secrets Agents can access credentials based on session config
Filesystem control Custom Go FUSE driver with per-file read/write policy, structured access logging, O(1) path-trie checks Standard Docker filesystem isolation
Approval workflows BCP approvals (bandwidth-constrained trust) + action approvals via REST API Three-tier tool approval (ask/record/ignore)
Audit trail Structured logs for file access, tool calls, message routing, and policy violations; queryable audit API Session transcripts (JSONL)
Human review Explicit review endpoint to reset taint on artifacts; risk manifest for file-level provenance Not formalized
Messaging platforms Matrix (via connector adapter; extensible base class for adding more) 22+ platforms (WhatsApp, Telegram, Signal, iMessage, Teams, etc.)
Web interface Real-time dashboard -- agent topology graph, classification matrix, log viewer macOS, iOS, Android with voice, camera, device integration
Browser control Headless Chromium with persistent host sessions (browser: true per agent) Chrome DevTools Protocol
Skills / plugins Skill files loaded at session start; FUSE-enforced -- undeclared skills are unreadable ClawHub marketplace (bundled, managed, workspace skills)
Deployment Docker / docker-compose (single-operator) Docker, Podman, Fly.io, Render, Cloudflare Workers, Nix, systemd, launchd
LLM support Claude (via Claude Agent SDK) Claude, GPT, DeepSeek, Gemini, and others

When to choose TriOnyx

You care more about what your agents know than what platforms they connect to. You want formal information flow guarantees, auditable provenance, and a non-agentic security boundary -- and you're willing to trade breadth of platform support and a large contributor ecosystem for those properties.

When to choose OpenClaw

You want the widest possible platform reach, native mobile apps, and a large community. You're comfortable managing security through capability restrictions and operational discipline rather than information-theoretic enforcement.