Quality Intelligence

for Modern Manufacturing

Loopr is an AI-powered Quality Intelligence System that helps manufacturers digitize inspections, automate visual quality control, and uncover systemic quality risks across plants, suppliers, and production lines.

Truck moving through an AI vision inspection line

Request Demo Start a 4-Week Pilot

No proprietary hardware.

Works with the cameras, tablets, and systems already on your floor.

Trusted By

Recognition

GEEKWIRE

Best AI in Startup of the Year

2026

SAFRAN

Safran Explore Startup Challenge

2024

SANDVIK

Sandvik Startup Challenge

2023

MARVIN

Selected Innovation Partner

2026

TRATON

Traton Startup Challenge

2026

wHAT lOOPR does

Software Is Only the Start. We Stay Through Adoption.

Loopr runs on the camera estate you already have parts coming in, parts being built, the people building them, and everything that comes back after. We integrate, we don't replace.

100%

Coverage

Inspection points

30%

Fewer escapes

20–30%

Less scrap & rework

AI visual inspection in a manufacturing plant

Ref

Capability

Where it happens

01.

Incoming Parts inspection

Three checkpoints

Three checkpoints, one record. Checks the part, the label of the part against specs, and surface defects logged at the station. Every part is inspected as it arrives, as it is built, and before it ships: logged, traceable and audit-ready.

1a.

Part Kitting

Confirms every kit is complete and correctly matched before it is released to the station.

Aerospace loose parts kit verified against its manifest

Fig. 1A

Part Kitting

Part Inspection

Checks each incoming part against spec. Surface and finish defects logged at the dock.

Aerospace part label read and identified by AI

Fig. 1b

Part Inspection

Inline Inspection

At the station, in the flow of work, not three operations later, when rework has multiplied.

Welding

Detects incomplete welds, porosity, spatter and missed joints as the weld leaves the cell.

Fig. 2a

Welding

Fig. 2b

Painting

Flags runs, orange peel, thin coverage and contamination on the painted surface before cure.

Vehicle hood assembly checked by AI inspection

Fig. 2b

Assembly Verification

Verifies the right components are present, and in the correct position. Works with integrations to ERP/MES or without. Active data capture and visual evidence of jobs done correctly, and evidence of proper rework.

Final Inspection

The last check before dispatch, producing a traceable record for every unit that leaves the plant.

AI visual inspection running on a production line

Fig. A3

Final Inspection

Safety monitoring

Monitor workplace safety in real time by identifying unsafe conditions such as missing safety harnesses, unsafe lifting, restricted-zone entry, and vehicle-related risks. Detect risks and trigger immediate alerts to prevent incidents and improve workplace safety.

Safety Harness Compliance

Spill Detection

Restricted-Zone Monitoring

Near-Miss Detection

Crane lifting a transformer in a warehouse

Fig. 03 — stand-in

Plant-wide Safety Monitoring

After-sales and MRO

Documents the condition of returned and serviced units, so teardown findings, repair evidence and warranty decisions sit on the same record as the original build inspection.

Faster Troubleshooting

Warranty decisions

Technician carrying out a service repair with AI-guided checks

Fig. 04 — stand-in

Return & service

Inventory management

Counts and locates stock visually across the floor and in storage, so what the system says you have matches what is physically there.

Visual counts

Location tracking

AI tracking inventory on warehouse shelves

Fig. 05 — stand-in

Floor & storage

Maturity journey

Four stages,
built with you.

Every manufacturer is at a different stage, but the path is the same: digitize the floor, automate the inspection, turn it into insight, then close the loop with agentic action. We build each stage with you, not around you.

Digitizing manual inspections on a tablet

Loopr quality analytics overview dashboard

AI agents running root cause analysis workflows

wHY lOOPR?

Software is only the start. We Stay Through Adoption.

Quality is a change in how a plant works, not a tool you bolt on. Loopr is built to land inside the systems, hardware and product mix you already run.

Loopr is not a standalone application.

It plugs into the MES, QMS and ERP already running your plant and gives you a visualization of the whole factory, rather than one more disconnected screen to check.

How inspection data flows through the Loopr platform

Fig. 11

Not standalone

Hardware and camera agnostic

Works with the fixed cameras, tablets, robotic systems, and PLCs already on your floor.

No rip-and-replace, no capital purchase to start pilot. Or No capital purchase gates the pilot.

Hybrid: on-prem or cloud

Runs where your data is allowed to live — fully on-premise, in the cloud, or split across both.

Defence and ITAR-adjacent programmes stay compliant.

Forward deployed engineering

Our engineers work on your floor, with your parts and your operators, until the system holds up in production.

The model is tuned on your parts, not a demo set.

Built for high-mix, low-volume

Most vision systems assume high volume and a clean bill of materials. Loopr assumes the opposite: many variants, short runs, and parts that change faster than the paperwork behind them.

No BOM dependency required.

measurable impact

What Structured Data Makes Possible

Once quality data is digitized and connected, the results compound from the manufacturing floor to the balance sheet.

100 %

Inspection coverage

10 x

Faster inspection

20 %

Lower quality cost

↓

10 %

Scrap & rework

3 x

Operator productivity

↓

10 %

Escape defects

Events

Meet Loopr in person

See all events

Upcoming22 October 2026 · 9:30 AM – 11:30 AMFactory AI Tour · AtlantaAtlanta, GA · with MicrosoftThe Era of AI in Manufacturing: executive insights, real-world use cases and 1:1 strategy sessions.

Microsoft x Loopr Factory AI Tour Detroit, October 21

Past event21 October 2026Factory AI Tour · DetroitDetroit, MI · with MicrosoftSee the event →

Past event

Roundtable seriesNov 2025 – Mar 2026 · 12 citiesThe Era of AI in ManufacturingWith Microsoft, across US Innovation HubsSee the recap →

Capabilities by role

One Structured System, Every Role

Mapped to every role, from the floor to the boardroom.

On the floor

Operators & inspectors

Digital workflows replace paper, capturing defensible, structured evidence at every step.

Shift level

Supervisors

Alerts, grounded in structured data your team can actually trust and act on.

“4.7% wrong headlights, 3rd shift.”

Enterprise

Management

Once the data foundation is in place, Copilot and AI agents can answer real questions. Defect trends, root cause, next action with dashboards for everything else.

Built on Azure OpenAI, Microsoft Fabric, Data Lake, and the Power Platform

Customer voices

What our customers say

Quality and operations leaders across automotive, industrial, and aerospace manufacturing.

Quality assurance

“

As a manager over our manufacturing facility, I can confidently say that Loopr's AI-generated inspection method has improved our approach to quality assurance. Before implementing this technology, we struggled with the occasional defect escaping our inspections, which affected our internal product quality. Since we adopted Loopr's system, we've achieved 100% inspection accuracy. The AI's ability to analyze and identify defects in real time has not only eliminated defect escapes but has also streamlined our inspection process, allowing our team to focus on other critical areas of production.

Chad Dole, Director of Operations, North America

Cascade Corp

Assembly line

“

Introducing the camera to the assembly line resulted in a greater value impact compared to merely addressing rework, as seen with traditional defect detection systems. Loopr's innovative ability allowed for the inspection of larger sub-assemblies, such as entire steering columns, directly on the production line rather than transferring them to a separate quality gate. We found that by incorporating an inspection step within the production workflow, there was a notable improvement in the yield of the assembly line.

Daimler Truck North America

Commercial vehicle manufacturing

Aerospace cabin interiors

“

Cosmetic defects remain a top quality concern in aerospace cabin interiors, and reliable detection, especially of microscopic paint flaws, is a persistent challenge. Loopr AI has proven its technology capable of addressing these complex needs, delivering effective microscopic defect detection and an impressive mobile inspection solution ready for immediate deployment. This mobile solution supports timely and consistent inspection of macro parts, making it well suited for both manufacturing and aftermarket environments. We are moving forward with scaling Loopr AI's solution across our US and Mexico sites. Their professionalism and deep manufacturing expertise make them a strong partner for Safran.

Bindioa Ouali, Director of Digital Transformations

Safran Cabins

Assembly line

“

Loopr took it upfront for the inspection of larger sub- assemblies, and since it is on average sitting directly on the production line rather than in the lab. Their flexibility to configure the system to our parts and process is the yield of the assembly line.

Quality Lead

Aerospace & defense manufacturer

Quality assurance

“

Loopr's fingerprinted inspection method has improved our approach to quality overview. The AI's ability to adapt and identify defects in real time has streamlined our inspection process, allowing our team to focus on other critical areas of production.

Head of Operations

Industrial equipment manufacturer

Aerospace cabin interiors

“

Loopr AI has a superb technology stack of addressing inner complex needs, delivering effective coverage. It is deployable in weeks and a modest operator overhead is easy for a handful of deployment lines increasing 12 weeks with as-built approach for a machine.

Director of Quality

Transformation, Global Cables

FROM PILOT TO FULL ROLLOUT

Four Weeks To
A Working Solution

The pilot isn't a proof-of-concept for its own sake: it's how we establish the platform and the model on your floor, fast, so Stage 1 (Digitization) has real trust and value to build on.

WEEK 0

Discovery & process

Understand the process, inspection requirements, systems, and deployment environment. Define the pilot scope, success criteria, and data collection plan.

WEEK 1

Data Collection & Forward Deployed Engineering

Start collecting data on the factory floor using tablets or camera systems. A forward deployed engineer works alongside your team to understand the process, capture real production scenarios, and identify edge cases.

WEEK 2

Data Labelling
& Preprocessing

Prepare the collected data for model training. Label images, organize datasets, and apply the required preprocessing to create a high quality training set.

WEEK 3

Model Training

Train the AI model using the prepared data. Evaluate its performance against the defined requirements and continue training as needed to improve accuracy.

WEEK 4 →

Deployment, Validation
& Refinement

Deploy the model in the production environment and validate it against real inspections. Refine the model using feedback and edge cases from the factory floor, then confirm readiness for scale.

Recent Blogs

View all

Agentic AI in Manufacturing Part 2: eight evidence layers feed a reasoning agent that produces a verified RCA draft, over a panel inspection photo

Agentic AI in Manufacturing, Part 2: From Defect Detection to Root Cause Intelligence

An illustrated technical case study of a proposed manufacturing reasoning agent.

Cover image: Hurdles enterprises need to overcome to operationalize AI

Hurdles That Enterprises Must Overcome To Adopt & Operationalize AI

AI is powerful but what are the hurdles that we need to overcome?

2024: Loopr AI’s Leap into Transformation

Loopr AI’s 2024 highlights include award-winning AI solutions, major milestones, and transformative innovations shaping aerospace and manufacturing.

An aluminium drive housing on a pallet fixture moving along a conveyor, with the production line behind it blurred by motion.

Why High-Speed Defect Detection Starts With a Better Image

See how motion blur, lighting, exposure and frame selection affect high-speed defect detection, and how to decide whether capture or AI needs attention.

Training AI Systems For Augmenting Human Visual Inspection

Learn more about how AI can speed up visual inspection and reduce errors

Start Your Quality Solution

Whether you're deep into a failed audit, an ERP/MES upgrade, or just tired of being told to “do something with AI,” the real first step is the same: structure the data. Let's talk about what that looks like on your floor.