Loopr AI: Funding, Valuation and Company Profile
Loopr AI develops software for manufacturing quality control, combining digital inspection workflows with AI-powered visual inspection and quality analytics. Its technology aims to help manufacturers identify defects, standardize inspection processes and use production quality data to improve operational decisions.
Visit Loopr AI ↗Basic Information
| Field | Details |
|---|---|
| Company Name | Loopr AI |
| Category | Industrial AI / Manufacturing Software |
| Founded | 2021, according to startup profile information |
| Headquarters | Greater Seattle area, Washington, United States, as reported in startup listings |
| Founder | Priyansha Bagaria, reported founder and CEO |
| Core Offering | Digital inspection workflows, visual defect detection and manufacturing quality analytics |
| Latest Reported Funding | Approximately $5.4 million seed round in 2025 |
| Valuation | Current valuation not publicly verified |
| Reported Investors | Growth Warrior Capital and Stellar Ventures have been associated with the reported seed round in startup databases |
| Website | loopr.ai |
What Loopr AI Does
Digital Quality Inspections
Loopr AI focuses on digitizing inspection procedures and quality records. Standardized workflows can help manufacturers improve traceability and make inspection results easier to review across production operations.
AI-Powered Visual Inspection
Computer vision can support visual checks of manufactured parts and assemblies, helping teams identify potential defects and reduce reliance on repetitive manual inspection alone.
Quality Data and Analytics
Digital quality information can help production teams review recurring defects, investigate potential causes and identify opportunities to improve manufacturing processes.
Key Products and Capabilities
Inspection Management
Digitizes inspection steps and records, giving teams a more consistent way to document checks and review results.
Visual Defect Detection
Uses computer vision approaches to support the identification of visual defects in components, products and assemblies.
Quality Documentation
Helps create structured inspection records that can support traceability, internal reviews and quality assurance processes.
Production Quality Insights
Enables teams to review quality information and look for patterns that may point to recurring manufacturing problems.
Process Standardization
Supports consistent inspection procedures across operators and production workflows, helping reduce differences in how checks are performed.
Workflow Integration
Digital inspection tools can help connect quality checks with existing manufacturing operations and reduce fragmented recordkeeping.
Manufacturing Quality Challenges
Manual Inspection
Repetitive visual checks can consume operator time and make inspection consistency difficult to maintain across shifts and facilities.
Defect Identification
Finding defects early can help prevent quality problems from spreading through production and reduce avoidable rework.
Disconnected Quality Data
When inspection information is scattered across systems or paper records, it can be harder to identify recurring issues and investigate their causes.
Inconsistent Procedures
Different inspection practices can make quality outcomes difficult to compare across production lines, operators and locations.
Production Rework
Earlier detection and better documentation can help teams investigate defects before they result in larger batches of affected products.
Limited Traceability
Digital inspection records can make it easier to review what was checked, what was found and where follow-up may be required.
Loopr AI at a Glance
Target Market
Manufacturers and industrial businesses seeking more consistent quality inspection and production workflows.
Technology Focus
Combines digital quality processes with AI and computer vision use cases in manufacturing.
Primary Application
Supports inspection, defect identification, quality documentation and production process improvement.
Who Can Use Loopr AI?
Quality Assurance Teams
Quality teams can use digital workflows to record inspection results, standardize checks and review recurring product issues.
Manufacturing Operations
Production managers can use quality information to investigate defects, monitor process consistency and identify areas for improvement.
Industrial Engineering Teams
Engineers can use inspection records and defect patterns to support root-cause investigations and process improvement initiatives.
Funding Journey
2021
Company Founded
Founded
Loopr AI’s founding year is reported as 2021 in startup profile information.
2025
Reported Seed Round
$5.4M
Startup databases report a seed round of approximately $5.4 million.
Valuation
Current Figure
Undisclosed
A current company-confirmed valuation has not been verified.