Agentic AI for manufacturing
Agentic AI you can put on a live production line
Describe a process and AI builds the shopfloor app in days, not months. Your team approves it before it reaches worker devices, every change is versioned, and you can roll back in one step.
Why agentic AI stalls before it reaches the line
Agentic AI goes a step beyond answering questions: it reads a document, decides what to do next and changes something in another system.
In an office
A wrong step means retracting an email.
On a production line
It can mean 83 parts built to an old torque spec, or a stopped line while someone works out what changed.
That's why most manufacturers are running agent pilots and very few have one acting on a live line.
>40%
of agentic AI projects expected to be cancelled by the end of 2027, citing rising costs, unclear value and weak risk controls
Gartner
80%
of AI projects fail before they scale, mostly for human and organisational reasons rather than technical ones
Fraunhofer
Most of these projects stall at the same point: the agent's output has nowhere controlled to land on the shopfloor, where it can be checked, approved, recorded and, if needed, undone.
On a live line, the most useful agent can't publish anything by itself
That restriction is what gets an agent past the pilot, because the people who own the line will only let AI near it when they can answer four questions. They're worth asking any vendor selling agentic AI to manufacturers, including us.
- Who approves a change before it reaches a worker?
Look for approval built into the system, so that nothing can skip it, rather than a policy document that says it should happen.
- Can you go back?
Every app and every change should be versioned, with a one-step rollback to the last version that worked.
- What's on the record?
What ran, when, and who approved it, captured automatically for every step.
- What can the agent touch?
Which systems it can read from and write to, and who decides that.
If any answer is "we're working on it", the agent stays in the pilot.
You might expect an approval step to cost the speed agents promise. On Workerbase, building, reviewing and approving happen in the same session, so the approval step doesn't slow you down: new apps still go live in days, not months.
Where Workerbase sits, between AI and the people doing the work
Answering those four questions takes a layer between the AI and the shopfloor. ERP plans production, MES schedules it, and AI can now draft the process, the app and the fix, but none of them make sure the work happens correctly at the station, shift after shift. That gap between the plan and what really happens on the shopfloor is where Workerbase has worked for years, at 40+ production sites in 19 countries.
Your team describes a process
A prompt, an SOP or a short video, or a request from your own AI agents (Claude, ChatGPT, Copilot) via MCP.
Workerbase AI assembles the app
From tested building blocks.
Workerbase: approve, version, run, record
Connected to ERP, MES, SCADA and PLC through 100+ integrations.
Workers run it
On tablets, phones and smartwatches. Execution data flows back into Workerbase.
With Workerbase AI, that's also where AI-built work goes live. You describe the process, AI builds the app, your team approves it, and workers run it on the devices they already carry. Every step is recorded, and Workerbase connects to the ERP, MES and PLM systems you already run through proven out-of-the-box integrations.
For your architects: Workerbase is the runtime for your shopfloor apps. It holds each app's state, checks that a worker has the right training and permissions before a task starts, and records every step.
Building blocks
How AI builds a shopfloor app without writing code for your line
When you describe a process, AI assembles the app based on the core elements of the Workerbase platform that are already tested and running in production:
- 1
Screens for the worker
The steps, inputs, photos and checks the operator sees at the station, on a tablet, phone or smartwatch.
- 2
Workflows and automations
The sequence, rules, escalations and triggers that drive the process.
- 3
Integrations
Reading and writing the data the process needs in your MES, ERP, SCADA or PLC, through 100+ out-of-the-box connectors.
- 4
Databases
Where the information the process captures is stored in Workerbase, structured and ready to analyse.
The building blocks come from years of shopfloor apps that our customers have built and run on live lines. Because AI only selects and configures blocks that are already proven, no AI-generated code reaches the line. A person can read and edit every app, and it's reviewed, approved and versioned exactly like an app your team built by hand.
01
Screens
What the worker sees
02
Workflows
Rules, escalations, triggers
03
Integrations
MES, ERP, SCADA, PLC
04
Databases
Structured shopfloor data
Your own agents
Connect the AI agents you already use
The same core elements of the Workerbase platform are open to the agents your teams already work with, whether that's Claude, ChatGPT or Microsoft Copilot, or agents running in n8n or Copilot Studio. Through the Workerbase MCP server (Model Context Protocol, the open standard for connecting AI agents to software), those agents can:
- ask what's happening on the floor right now: open tasks, escalations, shift status, asset history
- build shopfloor apps from a prompt, using the same core elements
- start workflows your team has already approved, for example an alarm response on a specific asset
Whatever an agent builds lands in the same approval step as everything else, so it can't put a new or changed app live on its own. It gets the same versioning and audit trail, and the roles you set decide which data and systems it can reach.
AI agent asks
workerbase.getShiftStatus({
plant: "line_4",
date: "today"
})Workerbase responds
Line 4 · Shift A · 6 open tasks. 2 overdue escalations. Last alarm: conveyor fault at 09:14, resolved in 11 min. Shift handover in 47 min.
AI agent builds
workerbase.buildApp({
prompt: "Line clearance checklist for line 4"
})Waiting for approval
Line clearance checklist · v1 · built by an external agent. Not live until your team approves it.
Live today
What AI does on Workerbase today
Builds shopfloor apps from a description
Describe a process in plain language, upload an SOP or a short process video, or ask from your own AI agent. You review the app, adjust it and approve it. Ops teams handle 85% of configuration within the rules IT sets.
Answers questions at the station
Workers ask in plain language and get answers from your manuals, SOPs and process notes, with the source shown.
Writes the shift handover and helps with troubleshooting
AI drafts shift summaries from what happened on the line, in the worker's language, and suggests troubleshooting steps based on past repairs.
Keeps every app under control
Each app is approved before it runs, every version is kept, rollback takes one step and the audit trail records everything. ISO 27001 certified, TISAX assessed, GDPR compliant.
What agents don't do on Workerbase
- They don't put anything live without approval from your team, whether the agent is ours or yours.
- They don't write code that runs on your line.
- They don't operate machines on their own. A workflow can write to a PLC or trigger a machine action, but only as a step your team configured and approved, and an agent can't add or change such a step without that approval.
- They don't replace your ERP or MES. They read from them and write back to them.
- They don't need a data lake first. You start with the systems you have.
Running on live production lines.
40+
Production sites
26,000+
Users
19
Countries
2 weeks
To take a first process live
“What used to take months can now be implemented in just a few days.”
Marco Eckert
Planner Site Planning Shopfloor-IT, Porsche AG