Artificial intelligence (AI) is an evolving technology that is still growing, but it is undoubtedly getting better. 

For all we know, factories might not even need lights 20 years later, because most of them will be operated by AI. We see a lot of R&D happening within the AI framework, giving good results. Besides, we see newer frameworks coming in. 

AI-based visual inspection, too, has been growing by leaps and bounds, reshaping automotive inspection. It helps examine detailed defects in vehicles, providing automotive OEMs the opportunity for accuracy and cost-savings. 

One such company focusing on AI-based visual inspection is Lincode Labs, whose AI-backed visual inspection solution, Lincode Visual Inspection System (LIVIS), is its current focus. The company was started with complete research and understanding of the top challenges that manufacturers globally face. After interviewing close to 100 customers, 86 percent of them said that quality inspection happens to be their biggest challenge.

“We were intrigued by this and went to various quality inspection people and identified the technology they were using,” says Rajesh Iyengar, Founder and CEO, Lincode Labs, and goes on, “We went on to find out that the technology hasn’t changed for two decades and there were a lot of false calls in it. That’s when Lincode stepped in and built a product around specific challenges focused on the automotive industry.”

Automotive OEMs, too, look at specifically reducing these false calls and improving productivity, which Lincode has helped solve through its AI-backed visual inspection solution. “The industry standards were 150 to 200 false calls per million inspections. So, in our case, we are doing it in zero to four parts per million,” Iyengar cites.  

Iyengar further reveals that due to this, 80 percent of their customers are repeat orders. “That’s because they are completely happy with the inspection process and the way the inspection is automated,” he mentions.  

LIVIS
Traditional vision systems cannot catch up with AI, as Iyengar says. He avers, “LIVIS stands out because we have built it as a platform. The scalability becomes easier if you’re going to deploy it across multiple factories and locations. But also, the foremost important thing is that it is completely made as a product. Thus, AI is commoditised. With the LIVIS platform, we can bring the cost and time to deployment down.” 

Lincode’s role in the automotive industry
What’s interesting is that even if Lincode caters to the manufacturing industry as a whole, it first addressed the automotive industry. The company researched the market size of various manufacturing companies and the automotive industry took the top spot, with close to USD 542 billion of global value.  

“We started with the automotive industry but pivoted later,” Iyengar tells us and continues, “So, instead of looking at just the automotive or any other industry, we turned our attention to steel, metal, plastic, glass etc. We basically went to the surface and saw how steel and metal are produced today. Whether it’s a CNC machining or forging or casting process, these are major processes used for any industry across the globe involving steel and metal. We understood that steel and metal are dealt with in the same way globally. Therefore, it made sense to go to the surface and into these kinds of defects specifically, and then generalise that and start building a model towards it. This, plus making AI as a product, has made deployment easier across the globe.” 

R&D centre in Bengaluru
Lincode recently opened a new R&D centre in Bengaluru, which also has a significant role to play in deploying the company’s solution across the world.

Stressing on the fact that evolving models are important in AI, Iyengar states, “It’s a continuous process; it’s not that you just build a model and you’re set. We have a big roadmap in the product development, and the Bengaluru R&D centre is going to play a major role in that. We are going to conduct deep research with various data collected across the globe and do various testing with that.” 

Staying ahead
What’s more, Lincode recently closed a funding round in December last year. Catering to a constantly evolving industry like the automotive, Lincode, too, strives to make sure that its visual inspection solution stays ahead and is put to use. “There are about more than 600 parts in a car and each part is segregated – like the structure, wiring, engine components etc.,” Iyengar shares and continues, “These segregations are made so that we can target the sector of the product. For example, when it comes to engine blocks, there is a specific model with a huge data set around engine blocks. This is how we stay ahead of competition.” Iyengar also adds that their trials with various use cases made them understand that inspection alone is not important but also the way the inspection is done. 

Essential skill sets for AI vision systems
Leveraging AI-based visual inspection solutions in the automotive industry is bound to increase productivity, and the cost of labour will also come down because of automation. “Today, most manufacturers use secondary inspection, which can be cut off straight away. This will improve their productivity and also reduce the risk of delays,” Iyengar enlightens. 

Moreover, AI vision systems come with their share of essential skill sets to bring out the best in the automotive industry. Iyengar states that, in general, skilling is required for the factory people. “This could be at various levels,” he puts across and adds, “It could be for the operators, the IT administrator or even the software development team. Hence, deep training is required, which can be somewhat cumbersome because it could be a bit challenging for the operator. So, an IT person might be needed in order to help the operator every time there is a downtime.” 

Covid-19 and AI-backed visual inspection
Such training or skills could certainly come in handy, because Iyengar claims that the need for AI-backed visual inspection solutions in the automotive industry has increased since the Covid-19 pandemic. “Unplanned shutdowns happened during Covid, because of which employees could not report and manufacturing could not continue properly,” he responds and adds, “Hence, a lot of investments are happening because of this. In fact, even now, a lot of employees are still not reporting and the labour problem has become global. It has become tough to get skilled workers. This has led to the adoption of autonomous manufacturing for automotives, where AI is going to play a big role.”

Meeting industry requirements
For an industry that is an economic force globally, AI-based visual inspection is certainly meeting the high-quality requirements of the customers of the automotive sector. Plus, we already see companies like Volvo using the technology. Safety surpasses any requirement, and this requirement can be fulfilled if quality is top-notch. And quality will be at its best if automotive manufacturers can perform production quality inspections in the most efficient way. (MT)

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Coretura, a 50:50 joint venture between Daimler Truck and Volvo Group, has entered into an engineering agreement with Accenture to accelerate the development of a software platform for commercial vehicles.

The company, headquartered in Gothenburg, Sweden, currently employs over 100 engineers. It continues to recruit specialists in system architecture, high-performance computing and cloud infrastructure to support its roadmap, which targets the delivery of its first commercialised products towards the end of the decade.

Coretura intends to create a single software platform, language and standard for trucks, buses and other heavy-duty transport vehicles. The platform is designed to support vehicle lifecycles of more than 15 years, moving the industry away from projects that require custom software development for each new vehicle.

As the engineering partner, Accenture will support development across several areas, including:

• Electrical and Electronic (E/E) architecture
• Software abstraction and hardware integration
• Embedded software, middleware, and cybersecurity
• Functional safety and cloud infrastructure

The platform aims to provide a reusable software stack to lower costs and standardise time-to-market for global manufacturers. For fleet operators, the system is designed to allow for continuous software updates and performance upgrades delivered over the air.

Johan Lunden, CEO, Coretura, said, “Our purpose is to advance mobility at the speed of ideas, and that takes depth. Building a full-stack SDV platform demands expertise across embedded software, middleware, cybersecurity, and functional safety, all designed for vehicles with lifecycles measured in decades. Accenture’s reinvention capabilities let us move faster without compromising the standards our customers depend on. This is acceleration, not course correction.”

Rainer Oder, SDV Embedded Software Lead, Accenture, added, “Helping the industry advance software-defined vehicles is a priority for Accenture. Our landmark collaboration with Coretura is designed to change embedded software engineering for automotive platforms. Together, we are looking to solve the challenges of a fully software-defined architecture – addressing critical areas such as hardware abstraction, API management and AI-based engineering optimisations.”

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The ePlane Company has announced the completion of its full-scale electric vertical takeoff and landing (eVTOL) aircraft, the e200X. Designated PT-01, the prototype has successfully integrated all core subsystems into a single structure, marking the transition from design and simulation to physical testing.

The e200X is designed as a single airframe versatile enough to serve three distinct markets – Passenger Air Taxi, Urban Cargo Carrier and Air Ambulance.

The company emphasises that the aircraft was designed to be compact, allowing it to integrate into existing urban infrastructure without requiring significant city redesigns.

Developed at the company's own facilities in Chennai, the e200X features in-house development of major components, including propellers, airframe structure, landing gear and battery pack.

This vertical integration provides the company with control over performance, manufacturing costs, and iteration speed, having reached this milestone on approximately USD 21 million in funding.

With assembly complete, the e200X will now undergo ground testing, flight testing and certification.

Prof. Satya Chakravarthy, Founder, The ePlane Company, said, "We set out to build an electric aircraft to a world-class benchmark, engineered and manufactured in depth in India for the World.  We deliberately designed the e200X to be compact, because an aircraft that asks a city to rebuild itself around it will not solve the problem it was built to solve. The same airframe can move people as an air taxi, carry goods as a cargo aircraft, and save lives as an air ambulance, and it can do all three using the infrastructure cities already have. That combination of real capability and capital efficiency is how we intend to compete, and win, in markets around the world.”

The company’s board includes prominent figures such as Vishesh Rajaram (Speciale Invest), Eash Sundaram (JetBlue) and Aditya Ghosh (Homage, Akasa Air). The venture, incubated at IIT Madras, has also received international recognition, including being showcased at Bharat Innovates 2026 and featured in Nvidia Founder Jensen Huang’s GTC keynote.

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Chinese technology company Xiaomi has marked a new milestone for its automotive product offering with its electric vehicle.

The company has announced a significant milestone in autonomous vehicle technology by completing the first official autonomous lap of the Nurburgring Nordschleife circuit in Germany with the Xiaomi YU7 GT, equipped with a Track Package, navigating the 20.8 km circuit without a human driver, recording a lap time of 10:29.483.

Following this performance, the Nurburgring has introduced a new official vehicle category: Autonomous Driving (under Electric Vehicles).

The Xiaomi YU7 GT autonomously navigated all 73 corners of the Nordschleife, managing 300 metres of elevation change and varying road surface conditions. The performance was driven by Xiaomi’s autonomous driving system, which integrates the Xiaomi XLA architecture and the MiMo-Embodied foundation model introduced in March 2026. The end-to-end architecture enabled the vehicle to coordinate steering, braking and power delivery in real-time, maintaining stability under high-speed and high-load conditions.

Xiaomi’s autonomous driving programme has evolved since the 2024 launch of Xiaomi HAD. The current system moves beyond simple behaviour imitation toward autonomous decision-making and deeper environmental interpretation. The company stated that the Nurburgring project serves as a critical testing ground to collect data for refining vehicle dynamics modelling, control strategy optimisation and safety redundancy mechanisms.

This achievement underscores Xiaomi’s commitment to advancing artificial intelligence in the automotive sector through rigorous real-world validation.

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QuantumScape Corporation has announced a multi-year joint research agreement with Honda R&D Co., a subsidiary of Honda Motor Co.

The collaboration focuses on advancing QuantumScape’s solid-state lithium-metal battery platform, including the development of associated manufacturing processes.

This agreement follows a successful technology evaluation period during which Honda conducted a technical study and competitive benchmarking of QuantumScape’s battery platform.

Atsushi Ogawa, Chief Operating Officer, Research Center of Excellence, Honda R&D Co, said, “QS technology demonstrated compelling and unique advantages during our evaluation. We see potential for QS technology to add value across a range of applications, including automotive, and we are excited to move forward into the next phase of our partnership.”

Dr. Siva Sivaram, CEO and President, QuantumScape, added, “Honda is a leading global automaker renowned for its engineering excellence and product quality across automotive and other applications worldwide, and its evaluation represents one of the most rigorous assessments of our technology to date. This agreement reflects the growing confidence in QS solid-state lithium-metal batteries to enable safer, higher-density energy storage.”

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