The Agent Fabric

Orchestrating distributed intelligence across data centers, edge nodes, and IoT devices

Real-time Coordination:

Watch autonomous agents collaborate through a distributed mesh network.

Category

Distributed Agent Infrastructure for Enterprise AI Automation

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.

Problem

Why AI automation fails at scale

  • 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

How the market is structured

Layer 4

AI Interfaces & Assistants

(chatbots, copilots — not our market)

Layer 3

Workflow Automation Platforms

n8n · Zapier · Make · Power Automate — we integrate, not compete

Layer 2

Agent Runtime & Orchestration (emerging)

Planning · Memory · Tool execution — mostly centralized today

Layer 1

Distributed Agent Infrastructure

Edge nodes · Gateways · On-prem · Hybrid · IT/OT integration · Sovereign

← The Agent Fabric operates here

Positioning

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

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

DimensionWorkflow PlatformsThe Agent Fabric
Primary focusTasks & workflowsInfrastructure & execution
DeploymentCloud-firstOn-prem, edge, hybrid
Integration modelAPIsNodes, gateways, local connectors
AI roleTool inside workflowsNative, distributed agents
ScaleLogical scalePhysical + logical scale
IT/OTLimitedCore capability
SovereigntyLowHigh

We do not replace these tools. We enable them to work at enterprise scale.

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.

Why now

Why this matters 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

Outcome

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

Positioning statement

One sentence

The Agent Fabric provides the distributed, sovereign infrastructure layer that allows AI agents to operate inside enterprise systems — securely, locally, and at scale.

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Contact

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