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AIIISS AI AGENTS
From “what happened”
to “what to do next”
For twenty years, manufacturing systems have recorded what happens on the shop floor. Agents go one step further with that data: they find problems, identify causes and propose solutions for people to approve.
WHAT CHANGES
The same machine alert, handled two ways
With systems only
People go looking for data
- The machine stops, an operator reports it, and only then does the shift lead find out
- The planner digs through the schedule and moves work orders by hand
- The quality engineer checks records afterwards to find affected lots
- The morning meeting reviews yesterday's reports
With AI agents
Data comes looking for people
- Abnormal vibration triggers an alert before the machine stops
- The planner receives a reschedule proposal together with its impact on due dates
- Potentially affected lots are already listed, waiting for a quarantine decision
- Review time goes into deciding what to do next
THE AGENTS
Every agent lives inside a business product
Agents read real business data on the platform and call the products' own business functions, so what they propose can actually be executed.
Process agent
Drafts work instructions from the BOM, routings and past documents, and lists the work in progress and inventory affected once an engineering change is released.
Which WIP is affected by this change?
R&D-to-manufacturing →Scheduling agent
Reschedules when rush orders, shortages or machine stops occur, and shows how each option affects due dates and work in progress.
If we insert this rush order, which orders will be late?
Advanced planning & scheduling →Quality agent
Watches every inspection from incoming to outgoing and, when something goes wrong, links it across people, machines, materials, methods and environment to give a traceability chain.
Which machine and material lot are behind these defects?
Quality & traceability →Lab agent
Assigns tests by method and staff qualification, reviews raw data automatically, and opens an investigation and drafts the report when results are out of spec or trending.
Which results in this sample batch need a second look?
Laboratory management →Equipment agent
Spots wear trends in live machine data and creates inspection and maintenance work orders before breakdowns happen.
Which machines are most likely to fail this week?
Equipment maintenance →Energy agent
Finds idle running, leaks and abnormal energy per unit, suggests moving loads off-peak, and compiles energy and carbon reports automatically.
Which line used the most energy per unit last month?
Energy management →Warehouse agent
Feeds the line at production pace and flags shortages and slow-moving stock early – less inventory, and the line never waits.
Is the material for tomorrow's work orders complete?
Warehouse & materials →Purchasing agent
Turns demand into purchase suggestions, compares past prices and supplier performance, and warns early about deliveries likely to slip.
Which purchase orders may not arrive next week?
Supplier collaboration →Logistics agent
Recommends load plans and carriers by volume and route, and when a shipment is delayed, estimates the new arrival time and notifies the customer and sales.
How do we combine these shipments to cut freight cost?
Transportation management →Sales agent
Gives a delivery date you can commit to before you accept an order, based on capacity and stock, and reminds you of opportunities to follow up and payments about to fall overdue.
The customer wants 2,000 units – what's the earliest we can deliver?
Customer relationship management →Service agent
Works out likely causes from the fault description and equipment history, dispatches an engineer by skill and distance, and gets the right spare parts ready.
Who should take this repair call, and with which parts?
Field service management →Finance agent
Generates vouchers from business documents, reconciles automatically at month end, and finds differences between documents and the books as well as unusual vouchers.
Which receivables don't match this month's shipments?
Finance →Data Q&A
Across every product, ask for output, yield, OEE, delivery, inventory or profit in plain language and get reports and dashboards without waiting for IT.
What was line 3's first-pass yield last week?
Book a demo →HOW THEY WORK
Sense, reason, recommend — then people decide
Agents never change production behind your back. Every step is backed by evidence, and every action needs approval.
- 01 SENSE
See what is happening
Machine data, work order progress, inspection results and inventory movements all come from the same platform.
- 02 REASON
Connect the dots
Agents combine history with process knowledge to identify causes and impact, and show their evidence.
- 03 RECOMMEND
Propose executable actions
Proposals map directly to actions in the system: reassign a work order, create an inspection, trigger replenishment.
- 04 APPROVE
People make the final call
Proposals go to the right role and are released only after approval. Everything is logged.
CONTROL
Safe to rely on, because the boundaries are clear
Permissions
The platform's permission model applies
- Agents can only see data the current user is allowed to see
- They can only start actions that role is already allowed to take
- Key actions require human approval before execution
Data
Every recommendation is traceable
- Each recommendation and its evidence is logged and can be reviewed
- The platform's existing security and data protection apply
THE FOUNDATION
Good agents start with good data
All Aiiiss ONE products share one set of master data, and machine data is cleaned before it is stored. Agents see a coherent picture of the whole plant instead of piecing it together across systems.
FAQ
About AI agents
What can Aiiiss AI agents do?
There are currently 13 agents covering every business domain: R&D and production (process, scheduling), quality and testing (quality, lab), equipment and energy (equipment, energy), supply chain and logistics (warehouse, purchasing, logistics), customers and service (sales, service), business and finance (finance), plus Data Q&A across all products (ask for output, yield, delivery, inventory and profit in plain language).
Will an agent change production on its own?
No. Agents only make recommendations and show their evidence. Key actions are sent to the responsible person and executed only after approval, and everything is logged.
Do we need every product before we can use agents?
No. Each agent relies on its corresponding products — for example, the scheduling agent uses APS and MES data. The products you have determine which agents you can use.
How is data kept secure?
Agents follow the platform's permission model and can only access data the current user is allowed to see. The platform's encryption, audit trail and backup mechanisms apply as well. System & data security
Next step
See the agents work on a real scenario from your plant
Tell us about the problem that costs you the most, and we will build the demo around it.