Agent
Agent
Ramp-Up Agent
Stabilize new lines and products faster.
Tracks performance from the first production runs, identifies recurring launch losses, and documents which countermeasures improve stability.
how does it work
how does it work
Summary
Tracks performance from the first production runs, identifies recurring launch losses, and documents which countermeasures improve stability.
use cases
New product introduction; Line launch; Ramp-up management
industries
Automotive
Electronics
Medical devices
Industrial equipment
IMPACT
Manufacturing work unfolds over minutes, across people, tools, parts, machines, stations, and process variants. Our systems combine temporal video understanding, process mining, typed process graphs, large teacher models, edge-deployed students, and human process expertise.
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Agent library
Agent library
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Or customise your agents on your own
Don't get stuck with pre-built agents. Built tailored and customise around your use case, systems, data, and shop-floor setup.
DESCRIBE YOUR AGENT
Build an agent that flags cycle-time drops on Line 3 and alerts the shift lead in Teams.
S/4HANA context
Build agent
Agent builder
Or customise your agents on your own
Don't get stuck with pre-built agents. Built tailored and customise around your use case, systems, data, and shop-floor setup.
DESCRIBE YOUR AGENT
Build an agent that flags cycle-time drops on Line 3 and alerts the shift lead in Teams.
S/4HANA context
Build agent
Agent builder
Or customise your agents on your own
Don't get stuck with pre-built agents. Built tailored and customise around your use case, systems, data, and shop-floor setup.
DESCRIBE YOUR AGENT
Build an agent that flags cycle-time drops on Line 3 and alerts the shift lead in Teams.
S/4HANA context
Build agent
Agent builder
Or customise your agents on your own
Don't get stuck with pre-built agents. Built tailored and customise around your use case, systems, data, and shop-floor setup.
DESCRIBE YOUR AGENT
Build an agent that flags cycle-time drops on Line 3 and alerts the shift lead in Teams.
S/4HANA context
Build agent
Daily operations
Run every shift
with better information
Almetra turns production data into daily guidance—helping teams start informed, stay ahead of issues, and act before small losses become bigger problems.
Almetra turns production data into daily guidance—helping teams start informed, stay ahead of issues, and act before small losses become bigger problems.
Start every day informed
Automated morning briefings summarize yesterday’s performance, rank the biggest losses, and prepare managers to ask the right questions in the stand-up.
Morning Briefing
Yesterday
OEE
72.4%
Output
1,240 u
Start every day informed
Automated morning briefings summarize yesterday’s performance, rank the biggest losses, and prepare managers to ask the right questions in the stand-up.
Morning Briefing
Yesterday
OEE
72.4%
Output
1,240 u
See every shift as it happens
Track hourly output, cycle times, staffing, and progress against target—without waiting for an end-of-shift report.
Shift Output
Live
Actual
Below target
See every shift as it happens
Track hourly output, cycle times, staffing, and progress against target—without waiting for an end-of-shift report.
Shift Output
Live
Actual
Below target
Know where to act next
Almetra detects meaningful deviations and sends contextual alerts through Microsoft Teams or email, so the right people can respond quickly.
Almetra · Microsoft Teams
now
Deviation detected · Line 3
Cycle time vs baseline
+14%
Matches 3 past events this month
Likely cause: tool wear · Station 4
Know where to act next
Almetra detects meaningful deviations and sends contextual alerts through Microsoft Teams or email, so the right people can respond quickly.
Almetra · Microsoft Teams
now
Deviation detected · Line 3
Cycle time vs baseline
+14%
Matches 3 past events this month
Likely cause: tool wear · Station 4
Where to focus this week.
Recurring losses. Evidence. A practical next step.
Empty-carrier losses
6 h 40
1
Cycle-time drift
5 h 10
2
Changeover losses
4 h 20
3
Where to focus this week.
Recurring losses. Evidence. A practical next step.
Empty-carrier losses
6 h 40
1
Cycle-time drift
5 h 10
2
Changeover losses
4 h 20
3
BEYOND AGENTS
An agent is only as smart as its context.
Almetra combines video, machine data, AI agents, and employee feedback into one living model of how production actually runs.
continious loop
1
COMPLETE FACTORY CONTEXT
AI video
Sees cycles, motion, interruptions, and work.
Machine data
Connects PLC, MES, ERP, faults, and downtime.
Employee feedback
Validates findings with the people who run the line.
ERP Systems
Connects orders, inventory, and production plans.
2
From CONTEXT LAYER to digital twin
One objective picture of the floor—continuously learning.
Every signal is connected, interpreted, and checked against manufacturing reality. The result is not another generic answer, but guidance your teams can trust and act on.
3
OPERATIONAL ACTION
Brief the shift
Start every stand-up with the losses that matter and the why attached.
Act in real time
Alert the right team when output drops or a station falls behind.
Improve what recurs
Prove root causes, prioritize fixes, and track the gains.
BEYOND AGENTS
An agent is only as smart as its context.
Almetra combines video, machine data, AI agents, and employee feedback into one living model of how production actually runs.
continious loop
1
COMPLETE FACTORY CONTEXT
AI video
Machine data
Employee feedback
ERP Systems
2
From CONTEXT LAYER to digital twin
One objective picture of the floor—continuously learning.
BEYOND AGENTS
An agent is only as smart as its context.
Almetra combines video, machine data, AI agents, and employee feedback into one living model of how production actually runs.
continious loop
1
COMPLETE FACTORY CONTEXT
AI video
Sees cycles, motion, interruptions, and work.
Machine data
Connects PLC, MES, ERP, faults, and downtime.
Employee feedback
Validates findings with the people who run the line.
ERP Systems
Connects orders, inventory, and production plans.
2
From CONTEXT LAYER to digital twin
One objective picture of the floor—continuously learning.
Every signal is connected, interpreted, and checked against manufacturing reality. The result is not another generic answer, but guidance your teams can trust and act on.
3
OPERATIONAL ACTION
Brief the shift
Start every stand-up with the losses that matter and the why attached.
Act in real time
Alert the right team when output drops or a station falls behind.
Improve what recurs
Prove root causes, prioritize fixes, and track the gains.
BEYOND AGENTS
An agent is only as smart as its context.
Almetra combines video, machine data, AI agents, and employee feedback into one living model of how production actually runs.
continious loop
1
COMPLETE FACTORY CONTEXT
AI video
Sees cycles, motion, interruptions, and work.
Machine data
Connects PLC, MES, ERP, faults, and downtime.
Employee feedback
Validates findings with the people who run the line.
ERP Systems
Connects orders, inventory, and production plans.
2
From CONTEXT LAYER to digital twin
One objective picture of the floor—continuously learning.
Every signal is connected, interpreted, and checked against manufacturing reality. The result is not another generic answer, but guidance your teams can trust and act on.
3
OPERATIONAL ACTION
Brief the shift
Start every stand-up with the losses that matter and the why attached.
Act in real time
Alert the right team when output drops or a station falls behind.
Improve what recurs
Prove root causes, prioritize fixes, and track the gains.
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