Zero-Loss Manufacturing
Made prescribes the exact action your operators need, before the line stops.
Backed by

DEMO · Predictive Actions
HIGH-SPEED PRODUCTION LOOP
ASEPTIC FILL & FINISH
PLANT LOSS DIAGNOSTIC
Enter your line profile and get a free estimate of your annual losses.
PLANT PROFILE
Industry
OEE world-class target: 65%
Shifts per day
2 SHIFTPRODUCTION & VALUE
LOSS PROFILE
ESTIMATED ANNUAL LOSS
USD$1.34M
/ day
$5.4K
/ month
$111.8K
5-year
$6.71M
Based on your parameters — validated against real PLC data during onboarding.
ESTIMATED OEE
Industry target
65%
78.3%
Annual Loss Breakdown
USDAVAILABILITY LOSSES
$225.0K
Revenue lost while lines are stopped due to unplanned breakdowns.
100 events/yr · 450 hrs lost
PERFORMANCE LOSSES
TOP$943.3K
Revenue lost from micro-stops and running below rated speed.
1.3% micro-stops · 15% speed gap
QUALITY LOSSES
$173.3K
Revenue lost from defective units that didn't pass first-time quality.
3.00% defect rate · FPY 97%
DIAGNOSTIC INSIGHT
Based on your inputs, your highest-impact loss driver is Performance — micro-stops & speed losses. Micro-stops are invisible on most plant dashboards. They accumulate silently across every shift.
DAILY COST
$5.4K
while your plant runs
Get your full plant loss report
Signal to Action
From edge telemetry to execution-ready prescription: three operational layers, one continuous loop.
Monitors every line, every shift, without interrupting operations. Delivers the exact action before the event becomes downtime.

DEPLOYMENT LAYER
ONE INTELLIGENCE, TWO PATHS
Industrial AI that adapts to the needs of your plant.
Both paths include the same intelligence
Choose Edge if…
Dedicated local AI for low-latency lines
Best for plants that need local vision, isolated compute, and deterministic response close to the machine.
Talk to our team →Choose API if…
Fastest path to pilot on existing infrastructure
Best for teams that want dedicated cloud, no token limits, and rapid rollout on the PC or server they already own.
- First 10 pilots: $0 API access
- Dedicated cloud included
- No token limits
Not sure which deployment fits your plant? We will map the right path with your team in one working session.
Talk to an engineer →ENGINE LAYER
OPERATIONAL INTELLIGENCE ENGINE
Transforms integrated plant telemetry into operational context, classified events, and prioritized risk ready for the Prescription Layer.
Notifications
WebAppWhatsAppSMSMailNotifications
WebAppWhatsAppSMSMailOperators
THE CORE ENGINE WHERE TELEMETRY BECOMES EXECUTION-READY PRESCRIPTION.
Operational Context Modeling
Understands line, station, and shift behavior as one interconnected system, not isolated signals.
Event Detection & Classification
Identifies anomalies and true operational drift, separating normal process variation from critical events with confidence scoring.
Action-Ready Risk Prioritization
Ranks events by potential impact and intervention window, producing a queue ready for prescriptive execution.
PRESCRIPTIVE LAYER
THE INDUSTRIAL AGENT
Turns Engine outputs into operator-ready actions: what to adjust, by how much, when to execute, and through which channel.
CONTEXTUALIZED OPERATING STATE
Consolidates signals by line, station, and shift into one actionable operating view.
PRIORITIZED RISK QUEUE
Ranks events by potential impact and intervention window so teams act on critical issues first.
PRESCRIPTIVE NEXT ACTION
Delivers what to adjust, by how much, and when, with expected impact for immediate operator execution.
Backed by

Backed by Founders, Inc. — investors behind Airbnb, Stripe, and Figma — to build the defining industrial AI company of this generation.
NVIDIA Inception partner. Made deploys with up to 67 TOPS of Jetson inference power for real-time detection and classification at the machine level.
Named by MIT Technology Review as one of the 35 most innovative technology companies globally in 2025.
Startup Chile portfolio company — accelerating Made's deployment across Latin American industrial manufacturing.
Blog · Field Intelligence
From The Plant Floor
Technical articles on industrial AI deployment: architecture patterns, real-world OEE results, and operator-level implementation guides.
New engineering articles will be published here.
Get field reports in your inbox
Architecture breakdowns, agent capability updates, and deployment case studies — for engineers and operators who build.
SUPPORT · FAQ
Frequently Asked Questions
General
What is MadeOS for manufacturing?
MadeOS is an operational intelligence system that connects plant signals, analyzes risk in real time, and delivers prescriptive actions to reduce unplanned downtime.
Does deployment require stopping production lines?
No. Deployment is staged with OT/IT teams and can roll out line by line while production remains active.
Where does MadeOS run?
MadeOS can run on dedicated edge compute for low-latency requirements and extend to cloud workloads where process tolerance allows.
For the Production Floor
Do I have to learn new software?
No. Made delivers instructions directly to your phone via WhatsApp, SMS, or email — whichever you already use. There's no dashboard to monitor, no login required on the floor. You receive a clear action: what to adjust, on which machine, and by how much.
What exactly does an alert look like? Will I know what to do?
Each alert includes three things: the anomaly detected (e.g., 'Solder paste volume dropping at Station 3'), the recommended action ('Reduce conveyor speed to 85%'), and the urgency level. You won't receive raw data or vague warnings — only actionable instructions.
What if I get an alert but can't act on it immediately?
Made tracks alert acknowledgment and escalates automatically if no action is taken within a defined window. Your supervisor or shift lead receives the same alert as a follow-up. Nothing falls through the cracks.
Can the system generate false alarms?
Made's engine separates normal process variation from genuine anomalies using confidence scoring — so it filters out noise before sending anything to you. During your pilot, alert thresholds are calibrated to your specific line to minimize false positives from day one.
Do I need to be in front of a screen to use this?
No. The system is designed for floor conditions — alerts reach you on your phone, in the channel you already use. If your plant uses shared tablets or operator panels, Made can also surface alerts there, but it's not required.
Integration & Security
Does Made integrate with my existing ERP or MES?
Yes. Made connects to your existing systems — including SAP, Oracle, Ignition, Wonderware, and custom MES platforms — via standard industrial protocols (OPC-UA, MQTT, REST API). We don't replace your stack; we sit on top of it. Our team handles the integration during the pilot so your IT resources stay focused on operations.
What happens to my OT data security?
Your operational data never leaves your environment without explicit control. Made supports on-premise deployment and air-gapped configurations for sensitive facilities. All data in transit is encrypted (TLS 1.3), and we follow IEC 62443 industrial cybersecurity standards. We sign an NDA before any deployment begins.
How long does onboarding actually take?
From signed agreement to first live alert: 2-3 weeks. Week 1 is sensor and data source mapping. Week 2 is model calibration and baseline learning on your specific line. Week 3 is supervised live operation with your team. Production is never paused during setup.
Do I need to hire technical staff to run it?
No. Made is designed so your existing operators and shift supervisors can act on its outputs without any technical background. The system is monitored and maintained by Made's team under your SLA. You receive outcomes — not infrastructure to manage.
What happens if Made fails during active production?
Made operates as a passive monitoring layer — it observes and advises, but never controls your machines directly. If Made goes offline, your production line continues without interruption exactly as before. We maintain 99.9% uptime SLA, with automatic failover and real-time alerting to our engineering team if any component becomes unavailable.
