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About Us
CareersBringing Computer Vision AI Solutions Across All Industries
LandingLens is an AI computer vision system that provides a roadmap to improve quality, efficiency, and productivity across all industries. See all AI and machine learning use cases by industry below.
Automotive
AI applications in the automotive industry use our computer vision platform, LandingLens, to solve automated inspection challenges previously thought impossible. These challenges include quality assurance of large assemblies with dozens of regions of interest and hundreds to thousands of acceptable variations with weld and paint analysis, and many other complex inspection applications. LandingAI’s AI/Deep Learning workflow simplifies the development of automated machine solutions that identify, classify, and categorize defects while improving production yield across the entire plant or globally.
AI Use Cases in the Automotive Industry:
Weld inspections, including EV batteries
Dispensing/coating verification
Glass/scratch inspection
Condition/asset-based monitoring
Electronics
Whether it is wafer critical dimensions, lead frame, solder reflow, or large PCB/SMT inspection, AI/deep learning vision solutions offer the power to inspect complex products with the most challenging stacked tolerances. When combined with the LandingLens AI/DL vision solution development and deployment workflow, electronics manufacturers can solve quality assurance applications previously thought impossible, easily add new products to existing AI/DL models, and leverage the workflow’s advanced process monitoring, feedback, and management functionality to achieve new levels of productivity.
Electronics Industry AI Use Cases:
Wafer and Die Inspection
Solder quality/SMT inspection
PCB build validation
Biotech/Pharmaceutical
A microparticle in a syringe can mean the difference between life and death. High-volume fluid test machines require dynamic measurement of relative volumes for accurate diagnostics to save millions of lives from early disease detection. LandingAI’s visual inspection workflow empowers teams and inspectors to build reliable AI models that solve problems previously considered impossible to automate for biotech companies.
AI Biotech Industry Applications:
Vial inspection
Cell counting
Cell sorting
Tracking, CFR 2.11 validation
Agriculture
While AI/deep learning computer vision systems have helped package and distribute food for decades, today computer vision is moving out of the processing plant and closer to the field. Machine learning applications in the agriculture industry are helping harvesters to optimize yields, minimize chemical applications for greatest return and sustainability; and take over dirty, dangerous, and difficult jobs such as weeding and picking. Today, LandingAI is partnering with farmers, aiding them with AI visual inspection tools that maximize crop yield and take pressure off the operator, all while improving revenue and return.
Agriculture Industry AI Use Cases:
Automated picking/weeding
Plant disease classification remediation
Product sorting/grading
Harvest optimization
Manufacturing
Every scratch, incomplete assembly, or defective part matters to the OEM’s bottom line. Identifying defects correctly and consistently is critical to production success. LandingAI’s LandingLens™ provides an AI/Deep Learning visual inspection development and deployment platform that helps OEMs, system integrators, and distributors to easily evaluate AI/Deep Learning model efficacy for a single application, or as part of a hybrid solution combined with traditional 2D/3D machine vision and robotic control solutions.
AI Use Cases in the Manufacturing Industry:
Assembly inspection/validation
Complex defect detection and classification
Process monitoring and yield improvement
Easily expand, modify, and deploy AI/deep learning solutions
Cost Reduction
Root cause analysis
