The Agent Fabric
Orchestrating distributed intelligence across data centers, edge nodes, and IoT devices.
Part of our Auto Agent Workflows pillar — This project provides the infrastructure layer for deploying autonomous AI agents at scale.
The Agent Fabric provides the distributed, sovereign infrastructure layer that allows post-human entrepreneurs to deploy AI agents inside enterprise systems—securely, locally, and at scale.
The Problem
AI automation fails at scale because it’s:
- Too centralized
- Too API-dependent
- Too cloud-only
- Disconnected from real infrastructure
- Unable to operate close to data, machines, and systems
To automate real operations, AI must be:
- Deployed locally and at the edge
- Embedded in infrastructure
- Distributed across environments
- Connected to IT and OT systems
- Governed, observable, and sovereign
Market Position
The Agent Fabric operates at Layer 2—the infrastructure layer that sits beneath workflows and applications:
- Layer 4: AI Interfaces & Assistants (chatbots, copilots)
- Layer 3: Workflow Automation Platforms (n8n, Zapier, Make, Power Automate)
- Layer 2: Agent Runtime & Orchestration ← We operate here
- Layer 1: Distributed Agent Infrastructure (edge nodes, gateways, on-prem, hybrid, IT/OT integration)
We sit beneath workflows and applications, inside the infrastructure layer. We do not compete on UI, templates, or no-code. We enable the substrate that makes large-scale AI automation possible.
What We Focus On
The Agent Fabric is not an automation tool. It is the infrastructure layer automation depends on. We focus on:
- Where agents run
- Where data lives
- Where decisions must be made locally
- Where systems cannot rely on SaaS APIs
- Where AI must be embedded, not bolted on
Architecture
Layered View
LAYER 4 — Applications & Workflows
n8n · ERP · MES · Analytics · Dashboards
LAYER 3 — Agent Logic
Planning · Reasoning · Policies · Tool usage (LLMs, rules engines, decision logic)
LAYER 2 — Agent Fabric (our domain)
Distributed nodes · Edge agents · Gateways · Secure communication · Observability · Control planes
LAYER 1 — Infrastructure
Factories · Vehicles · Energy systems · Servers · Networks · IoT devices · OT + IT environments
Most companies build at Layer 4. Some experiment at Layer 3. Almost no one owns Layer 2. That is our position.
Privacy & Sovereignty
You own and govern your agents entirely inside your infrastructure—no external control plane, no hidden data egress, and full offline/local execution where required.
Comparison: Workflow Platforms vs The Agent Fabric
| Dimension | Workflow Platforms | The Agent Fabric |
|---|---|---|
| Primary focus | Tasks & workflows | Infrastructure & execution |
| Deployment | Cloud-first | On-prem, edge, hybrid |
| Integration model | APIs | Nodes, gateways, local connectors |
| AI role | Tool inside workflows | Native, distributed agents |
| Scale | Logical scale | Physical + logical scale |
| IT/OT | Limited | Core capability |
| Sovereignty | Low | High |
We do not replace these tools. We enable them to work at enterprise scale.
What We Enable
- Deploy AI agents inside infrastructure
- Connect agents across sites and environments
- Keep data local while enabling global coordination
- Run sovereign, offline/local-first when required
- Automate operations, not just tasks
- Prepare infrastructure for the next decade of AI
- Operate securely, locally, and at scale
Why Now?
AI automation is moving from:
- Experiments → operations
- Copilots → autonomous systems
- SaaS → embedded infrastructure
This shift needs a new foundational layer because:
- Centralized AI does not scale operationally
- APIs are not infrastructure
- Autonomy requires proximity to systems
- Sovereignty, privacy, and observability are non-negotiable
Positioning Statement
The Agent Fabric provides the distributed, sovereign infrastructure layer that allows AI agents to operate inside enterprise systems—securely, locally, and at scale.