Landing AI Receives Funding to Promote AI in Automotive and Electronics with Latest Platforms

November 18, 2021 by Seth Price

Landing AI recently received $57 million Level A funding from McRock Capital to develop AI systems for automotive and electronics manufacturing.

But what do they plan to do with this new round of funding? Landing AI aims to make artificial intelligence (AI) available for all industries, not just tech giants, but also for smaller manufacturing facilities.

McRock Capital invests in companies related to the AI industry. Scott MacDonald, Co-founder and Managing Partner of McRock Capital, mentioned, “We partner with relentless entrepreneurs...who bring transformative digital technologies to large industrial markets.”  

Data-Centric Approach

One of the key goals of Landing AI is to make the most from data. While other AI companies focus on generating big data with lots of data points, Landing AI is focused on generating high-quality data instead. 


landing ai

An engineer using LandingAI's LandingLens interface. Screenshot used courtesy of LandingAI


“You don’t always need big data to win with AI. You need good data that teaches AI what you want it to learn. AI built around 50 million data points doesn’t work when you only have 50 data points. By bringing machine learning to everyone regardless of the size of their data set, the next era of AI will have a real-world impact on all industries,” commented Andrew Ng, founder, and CEO of Landing AI. 

They aim to work with industry, using the data they already have to start training AI to improve their facilities. AI systems ultimately need to be developed by not just AI experts but process experts as well.

The company claims they already see results based on this approach. With this data-centric model, they are allegedly seeing a 67% increase in inspection accuracy, a 65% quicker deployment time, and a 40% improved yield in processes. 



Landing AI’s new product is LandingLens, an advanced machine vision tool for quality control in manufacturing lines. The system consists of three steps: data analysis, modeling, and deployment. LandingLens works with the customer’s data to build a defect book referenced by the AI when inspecting parts designed to speed up troubleshooting efforts.


Defects in steel sheet are found using machine vision and Landing AI’s approach. Image used courtesy of Landing AI


Once the defect book is created, users can upload the data to the company’s cloud for management and labeling. From there, one can use the datasheet to develop a model and train the AI. Then, the model is ready to be deployed so that defects can be spotted automatically.

LandingLens could be particularly helpful for distinguishing actual defects from “false positives” due to changing light conditions. This is specifically designed for plants or factories with large windows where the lighting changes minute to minute as clouds drift overhead. This could also work for plants that operate 24 hours a day, where diurnal lighting differences can wreak havoc on AI vision systems.


Use of Funds

This funding will be largely used to expand their engineering, sales, and marketing team. Ultimately, their catalog of capabilities is projected to grow as they up-train more engineers to work on these products. They plan to focus on sectors of manufacturing such as electronics, food and beverage, building automation, and more. 



LandingLens platform inspecting vehicles on an automotive assembly line using AI. Screenshot used courtesy of LandingAI


Landing AI is looking to expand its talent pool and has quite a few open positions for engineers. They are hopeful that this new funding will help them develop AI tools for factories of the future.