Industrial AI, Governed and Built In
The platform is the control plane. AI is the accelerator.
AI capability is table stakes in 2026. Governed access to your operations is the difference.
Every way AI shows up in your operations
From accelerating how you build, to acting inside live flows, to connecting the AI your company already trusts. Each one runs on the same governed platform.
01 Build
Accelerate engineering
FlowFuse Expert turns intent into working industrial applications, right in the editor.
Generate and edit Node-RED flows, Function node JavaScript, SQL queries and dashboard UI from plain language, and ask Expert to explain any existing flow so any engineer can pick it up. It works inline in the editor your team already uses, so there is no separate tool to context-switch into. That turns unfamiliar or inherited flows into something the whole team can read and maintain.
Describe the application you need and FlowFuse Expert agentically builds the starting flows and logic directly in your workspace. You begin from a working draft instead of a blank canvas, then refine it like any other flow. Everything it creates stays inside the platform, so the same permissions and review apply from the first node.
Start from an agent blueprint, like the LLM chat agent or RAG chat agent, to stand up a task-specific AI agent grounded in your own data, tools and context. It gives you a proven structure to adapt rather than wiring an agent up from scratch. With MCP servers you can give the agent access to anything, including your RAG applications. Because it runs on the platform, the agent operates within the access you grant it.
A chat assistant with answers grounded in FlowFuse and Node-RED documentation, so guidance comes from the product, not stale wikis. Ask how a node works or how to approach a build and get an answer without leaving your workspace. It shortens the path from question to working flow for new and experienced users alike.
02 Operate
Operate with AI, safely
AI that acts inside your flows and answers questions about live operations, always behind your controls.
Platform Automations let AI act on live systems, with every write behind an approval card, session-scoped and fully audited. A person approves, edits or rejects each proposed change before it reaches a machine. Nothing runs outside the permissions and RBAC that already govern your teams.
In Insights mode, ask questions in natural language and get answers grounded in live machine state, alarms and logs. Operators and engineers can check what is happening on the floor without building a report or querying a database by hand. Table and MQTT-broker reading are coming soon.
Run ONNX vision models inside flows next to the machine, with camera ingest over RTSP, for inference that works offline and keeps data on your network. Detection results flow into the same logic as any other signal, so you can trigger alerts or actions from what the model sees. Running at the edge means no round trip to the cloud and no image data leaving the plant.
Certified LLM nodes bring OpenAI, Anthropic, Gemini or local models via Ollama into any flow with your own keys. Choose the provider that fits each task, or keep everything on local models when data cannot leave your network. Because you supply the keys, model access and spend stay under your control.
03 Connect
Connect and govern your AI
Give the AI your company already trusts a governed door into operations, on a boundary you control.
Expose flows as MCP tools so the AI your company already sanctioned, like Claude or Copilot, can reach operational data through a permissioned boundary. The AI reaches only what you expose, on the terms you set, rather than getting direct access to plant systems. This is our most-requested capability and is in active development.
Build your own MCP servers and let Insights-mode agents call your tools and services as part of a workflow. Wrap an internal API or system as a tool once, then let agents use it wherever it fits. The agent stays inside the workflow you designed, calling only the tools you register.
Governance you can prove
The control plane every AI action runs through, the same one that governs your teams.
Approval cards on writes
Every write action AI proposes waits for a human to approve, reject or edit.
Per-tool permissions
Grant read, write or delete per tool and per team, so AI only reaches what you allow.
Role-based access
The same RBAC that governs your teams governs what AI can see and do.
Audit on everything
Every action AI touches is logged, so you can show exactly what happened and when.
Where AI meets your operations
The use cases pair with FlowFuse AI, from governed agent access to AI-assisted monitoring.
