The Distributed
Agentic OS

Deploy autonomous AI agents across your infrastructure. They write code, run tests, and fix bugs across every machine you own.

Request Early Access How It Works
Self-hosted
Privacy-first
Runs on your hardware
eigenclaw
$ eigenclaw start Starting EigenClaw Agentic OS... Memory: vector search + knowledge graph Mesh: 4 nodes online · encrypted Models: local (8B), GPU (72B), cloud (fallback) Ready → http://localhost:3000 › Add rate limiting to all API endpoints routing to gpu-server... read api/middleware.py ✓ read api/routes.py ✓ write api/middleware.py ✓ 84 lines write api/rate_limiter.py ✓ 62 lines write tests/test_rate_limit.py ✓ 45 lines bash pytest tests/ ✓ 23 passed Done. 2 modified, 2 created
Capabilities

An operating system
for autonomous agents.

Agents that take action across your entire infrastructure, remember what they learn, and improve with every interaction.

Agents that do the work.

Give an agent a task and walk away. It reads code, writes files, runs tests, and iterates until the job is done.

  • Multi-step execution with automatic error recovery
  • Reads, writes, and runs code autonomously
  • Watch progress in real time as agents work
  • Set guardrails for iteration limits and stop conditions
› Refactor auth to use encryption
routing to best available node...

read src/auth/middleware.py ✓
write src/auth/middleware.py ✓ 47 lines
write src/auth/encryption.py ✓ 32 lines
test pytest tests/auth/ ✓ 12 passed

Done. 3 files modified, all tests passing

The right hardware for every task.

Tasks automatically route to the best available machine. Heavy work goes to GPU servers, quick fixes stay local, edge tasks go to small devices.

  • Automatic routing based on task complexity
  • Works across any mix of hardware you have
  • Encrypted mesh networking between all nodes
  • Scales from one laptop to a fleet of servers
Mesh Status

gpu-server gateway · large model ● online
macbook worker · local model ● online
edge-device edge · small model ● online
cloud overflow · on demand ● standby

Encrypted · zero-config · auto-discovered

Agents that understand your systems.

Every interaction extends a knowledge graph of your codebase. Agents learn which files relate to which features, what decisions were made, and why.

  • Automatically extracts entities and relationships
  • Tracks files, bugs, decisions, and dependencies
  • Traverses connections to find related context
  • Scales from solo developer to large teams
Knowledge Graph

auth_middleware.py ─ HAS_BUG → plaintext-tokens
plaintext-tokens ─ FIXED_BY → use-encryption
auth_middleware.py ─ IMPORTS → encryption.py
encryption.py ─ CONTAINS → encrypt_token()

5 entities · 4 relations · auto-extracted

Memory that persists across sessions.

Agents recall relevant context from past work. Similar problems surface automatically. Old knowledge consolidates so context stays fresh.

  • Fast similarity search across all past interactions
  • Each project gets its own isolated memory space
  • Important memories surface first, old ones fade
  • Consolidation keeps context relevant over time
Memory Recall

query: "auth middleware encryption"

0.95 Fixed auth bug, applied encryption
0.82 Added rate limiting to API endpoints
0.71 Refactored database connection pooling

142 observations · 23 decisions · 8 projects

Every execution in a security boundary.

Every tool execution runs inside a sandbox. You control what each node is allowed to do. Full audit trail of every action taken.

  • Container-level isolation on supported hardware
  • Per-node security policies you define
  • Full audit log of every tool execution
  • Remote sandboxing for clients without GPUs
Security Policies

gpu-server sandbox: container policy: full access
macbook sandbox: process policy: restricted
allowed: read, write, test, list
edge-device sandbox: process policy: read-only
allowed: read, list

The right model, automatically.

Simple tasks use small, fast models. Complex work routes to larger models or cloud APIs. You set the rules, EigenClaw handles the rest.

  • Complexity-based model selection
  • Local models run at zero cost on your hardware
  • Automatic load balancing across nodes
  • Cloud fallback when local capacity is full
Model Routing

"Fix the typo" → fast · small model · local
"Write unit tests" → standard · mid model · local
"Refactor auth system" → heavy · large model · GPU
"Design architecture" → frontier · cloud API

Automatic · complexity-based · per-task

Your agents, wherever you are.

Access EigenClaw through the interface that fits your workflow. Web, desktop, mobile, or the messaging platforms your team already uses.

  • Web dashboard with full agent console
  • Native desktop app coming soon
  • Mobile app for iOS and Android coming soon
  • Telegram bot integration
  • Slack and WhatsApp coming soon
Interfaces

● Web Dashboard full agent console
● Telegram bot integration
○ Desktop App macOS, Linux, Windows
○ Mobile iOS, Android
○ Slack workspace integration
○ WhatsApp business API

● live   ○ coming soon
Infrastructure

Your hardware. Your rules.

Every machine you own becomes part of one agent mesh. Tasks route to the best available hardware over your private network.

Worker
Any Mac or PC
Apple Silicon, AMD, Intel
Local models via Ollama
Gateway
GPU Server
NVIDIA, AMD, or cloud
Large models via vLLM
Edge
Edge Device
Jetson, RPi, any SBC
Small models, low latency
Connected via Tailscale · encrypted · zero-config
Get Started

Running in three commands.

No cloud accounts. No API keys for local models. No telemetry. Just your hardware and your agents.

Install

One package. Works on Linux, macOS, and any machine with Python 3.11+.

pip install eigenclaw

Connect

Add nodes over Tailscale. DGX, Mac, Jetson, cloud VMs. Anything with SSH. They discover each other automatically.

eigenclaw mesh join

Deploy

Open the dashboard and start giving work to your agents. They pick the right node, the right model, and get it done.

eigenclaw start

Get early access.

EigenClaw is in private beta. Join the waitlist to deploy autonomous agents across your infrastructure.

No spam. We'll reach out when your seat is ready.