Zero-Loss Manufacturing

No failure is random.

Made prescribes the exact action your operators need, before the line stops.

Backed by

Founders, Inc.NVIDIA InceptionMIT Technology ReviewStartup Chile
ASEPTIC FILL & FINISH//
PRECISION PCB ASSEMBLY//
HIGH-SPEED BOTTLING//
MINERAL PROCESSING PLANT//
INJECTION MOLDING TELEMETRY//
ASEPTIC FILL & FINISH//
PRECISION PCB ASSEMBLY//
HIGH-SPEED BOTTLING//
MINERAL PROCESSING PLANT//
INJECTION MOLDING TELEMETRY//

DEMO · Predictive Actions

HIGH-SPEED PRODUCTION LOOP

ASEPTIC FILL & FINISH

Fill levelSterilization tempContainer integrity
00
01

DEPLOYMENT LAYER

MadePRODUCTION-READY INFRASTRUCTURE

Your Gateway runs on-site, speaks every protocol your plant already uses, and scales line-by-line — without a planned shutdown.

Made gateway installed inside an industrial control cabinet.

Universal Edge Ingestion

Connects PLCs, sensors, cameras, and MES into one multi-protocol operational telemetry layer, then scales line-by-line across the plant without stopping production.

Nvidia Edge Inference Power (up to 67 TOPS)

When minimum latency is required, Made deploys on-site hardware with up to 67 TOPS of NVIDIA inference power for real-time detection, classification, and prioritization of operational events.

Resilient Edge-to-Cloud Execution

When process tolerance allows, workloads run with multi-cloud, multi-region, and auto-scaling architecture.

Health checks, failover paths, escalation protocols, and OT/IT cybersecurity controls keep operations stable during rollout and after go-live.

02

ENGINE LAYER

MadeOPERATIONAL INTELLIGENCE ENGINE

Transforms integrated plant telemetry into operational context, classified events, and prioritized risk ready for the Prescription Layer.

Factory Inputs: Cameras, Sensors, Machines
Gateway
MadeOS

Notification System

MadeOS

WhatsApp

SMS

Mail

Customizable

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.

03

PRESCRIPTIVE LAYER

MadeTHE 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

Founders, Inc.

Backed by Founders, Inc., the firm behind Airbnb, Stripe, and Figma, to build the defining industrial AI company.

NVIDIA Inception

Backed by NVIDIA Inception to accelerate deployment of edge-native industrial AI.

MIT Technology Review

Recognized by MIT as one of the 35 most innovative companies of 2025.

Startup Chile

Backed by Startup Chile to scale high-impact industrial technology across Latin America.

IMPACT OF UNPLANNED DOWNTIME

25h/mo

UNPLANNED DOWNTIME

$129M

AVG. DOWNTIME COST

11%

ANNUAL REVENUE AT RISK FROM DOWNTIME

Source: Siemens, The True Cost of Downtime 2022 (published 2023)

The gap between your OEE and industry benchmark has a precise dollar value. Calculate yours below.

PLANT LOSS DIAGNOSTIC

What Is Your Plant Actually Losing?

Enter your production data. Get a real-money breakdown of what downtime, speed loss, and defects are costing you — in seconds.

PLANT PROFILE

Industry

OEE world-class target: 65%

3 lines
1 line20 lines

Shifts per day

2 SHIFT

PRODUCTION & VALUE

(units/hr per line)
1.0K u/hr
100 u/hr10k u/hr
USD · per unit
$0.50
$0.10$50
(% of rated capacity)
85%
50%100%

LOSS PROFILE

(per week, all lines)
2/wk
0/wk15/wk
1.5h
15 min8 hrs
(per line, industry avg: 8-20)
12/hr
0/hr60/hr
4 sec
1 sec30 sec
(% good units on first pass)
97%
70%100%

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%

A — Availability96.3%
P — Performance83.9%
Q — Quality97.0%

Annual Loss Breakdown

USD

AVAILABILITY LOSSES

$225.0K

17%

Revenue lost while lines are stopped due to unplanned breakdowns.

100 events/yr · 450 hrs lost

PERFORMANCE LOSSES

TOP

$943.3K

70%

Revenue lost from micro-stops and running below rated speed.

1.3% micro-stops · 15% speed gap

QUALITY LOSSES

$173.3K

13%

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

Blog · Field Intelligence

MadeFrom 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.

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.