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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Tier 1 automotive supplier Marelli has received the ‘Commendable’ honour in the ‘Engineering Product of the Year’ category at the Digital Engineering Awards 2026. The ceremony, hosted by L&T Technology Services in association with ISG and CNBC-TV18, was held in Boston, USA, on 12 March 2026.

The award recognises the role of Marelli’s Zone Control Unit (ZCU) in the transition towards software-defined vehicles.

The ZCU is designed to replace traditional domain-based architectures with a platform that delivers cross-domain control through a single Electronic Control Unit (ECU). This system simplifies vehicle electrical and electronic (E/E) layouts and enables communication across vehicle zones. By reducing the number of dedicated ECUs and streamlining wiring, the ZCU reduces wiring harness weight by 30 per cent compared to existing systems.

It is built on the EliteZone platform and supports ethernet capabilities, hardware accelerators, and remote-control protocols. It features processing performance up to 6 KDMIPS, two-port Gigabit Ethernet, and more than 20 CAN and LIN interfaces. The unit also includes an integrated hypervisor and data routing engine, supporting functional safety up to ASIL D standards.

For power management, the ZCU accommodates 48V system requirements with dedicated power input and efuse-protected output. The hardware uses a service-oriented architecture (SOA), which decouples software development from hardware. This approach allows modules to subscribe to services exposed by the ECU, supporting feature updates throughout the vehicle lifecycle and shortening development cycles for manufacturers.

Ravi Tallapragada, President, Marelli’s Electronics business, stated, “This recognition for our Zone Control Unit makes me and all of us at Marelli truly proud. It reflects the impact of our work on supporting the industry’s transition toward software-defined vehicles. By bringing cross-domain control into a single, scalable platform, our ZCU enables vehicle makers to innovate at speed. I want to congratulate our global engineering teams, whose dedication and expertise made this achievement possible.”

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drivebuddyAI has been awarded a patent for a facial recognition system designed for vehicle environments. The technology identifies drivers in moving vehicles to monitor duty hours and manage fatigue.

The system uses computer vision and artificial intelligence to recognise faces under varying lighting conditions and when drivers wear accessories such as caps or mufflers. This replaces manual or key-based identification methods to track driving time for wage calculations and safety compliance.

The patented technology is integrated into several areas of the company's product suite:

• Driver Profiling: Used in the 'CARDs' scoring method.
• Alert Systems: Provision of language-specific alerts based on driver identification.
• Performance Monitoring: Real-time tracking of duty time and driver behaviour.
• Compliance: Alignment with Indian government discussions on enforcing rest periods for commercial vehicle operators.

The company holds 15 patents in AI vision, edge processing, and risk assessment. Its systems meet India's AIS-184 driver monitoring standards and the European Union's General Safety Regulation (GSR) 2144.

Nisarg Pandya, CEO, drivebuddyAI, said, “Driver fatigue remains one of the most critical yet under-addressed causes of highway accidents. Our patented technology ensures that fleets know exactly who is driving, for how long, and under what conditions. This creates a foundation for enforcing safe driving limits while also enabling continuous learning and improvement for drivers. This milestone reflects our commitment to delivering technology built from the ground up and leveraging AI to enable safer and smarter driving solutions.”

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Servotech Renewable Power System and Electra EV have been granted a patent by the Indian Patent Office for an ‘Electric Vehicle Charging Device’. The technology is designed to provide charging solutions for low-voltage electric vehicles (EVs).

The device addresses interoperability challenges by enabling fast DC charging for low-voltage EVs with sub-200V DC platforms. This includes vehicles based on GB/T Bharat DC 001 standards. The technology allows these vehicles to utilise widely deployed, conventional high-voltage CCS2 charging infrastructure.

The patented device incorporates power management and voltage conversion systems to facilitate energy transfer to low-voltage battery platforms. The primary focus of the technology is on vehicle segments such as small commercial EVs and pick-up vans, which are used for urban and last-mile mobility.

Key features of the technology include:

• Interoperability: Enables sub-200V DC platforms to use CCS2 fast-charging stations.
• Compatibility: Supports vehicles adhering to GB/T Bharat DC 001 standards.
• Energy Management: Advanced voltage conversion to ensure safe battery charging.
• Safety: Integrated protocols for stable energy transfer.

The joint ownership of the patent by Servotech and Electra EV is intended to accelerate the development of charging infrastructure for small commercial fleets. The demand for such flexible solutions has increased as adoption of low-voltage EVs grows within the Indian logistics and transport sectors.

Arun Handa, CTO, Servotech Renewable Power System, said, “Securing this patent is an important step in strengthening our innovation-led approach to EV charging technology. Low-voltage electric vehicles are a key part of India’s mobility ecosystem, particularly in segments like small commercial fleets. This patented device has been designed to ensure safe, efficient, and reliable charging for such vehicles, helping make EV adoption through improved charging compatibility.”

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NXP Semiconductors has launched the NXP CoreRide Z248, a zonal reference system combining 48V energy distribution with data routing. The hardware-software foundation is designed to assist OEMs and Tier 1 suppliers in transitioning to software-defined vehicle (SDV) architectures by reducing integration effort and development cycles.

The Z248 is built on NXP’s S32K5 microcontroller series, featuring on-chip Magnetic Random Access Memory (MRAM). This technology is intended to accelerate electronic control unit (ECU) programming during manufacturing and over-the-air (OTA) updates.

The system integrates several 48V-capable components and networking tools:

• Power Management: Includes eFuses, Power Management Integrated Circuits (PMICs), and DC-DC converters for energy conversion and protection.
• Networking: Features Ethernet PHY and CAN transceivers for data handling.
• Software Stack: A pre-validated stack managing smart data energy network (SDEN) functions such as impedance monitoring and diagnostics.
• Safety: Built-in functional safety and real-time responsiveness for zonal processing.

NXP stated it has validated the Z248 through system-level tests focusing on low-power modes and wake-up response times. The package includes a Board Support Package (BSP) with integrated software from partners including GLIWA for performance monitoring, Green Hills Software for compilers and Vector for embedded tools.

The reference system is designed for deployment across internal combustion engine (ICE), hybrid, and battery electric vehicle (BEV) platforms. It supports ECU consolidation by managing energy distribution and data protocols within a single architecture.

Sebastien Clamagirand, SVP and General Manager, Automotive Systems & Platforms, NXP Semiconductors, said, “The NXP CoreRide zonal reference system Z248 delivers a performance-optimized, scalable 48 V foundation that intelligently fuses power, data and software, while dramatically simplifying system integration, reducing time to market, and enabling OEMs to focus on vehicle differentiation and long‑term value creation.”

Peter Gliwa, CEO and Founder, GLIWA, added, “NXP understood that the eco-system, the tooling around a new platform is essential for its success. With our Analysis Suite T1 built into the NXP CoreRide Z248 zonal reference system, high efficiency, proper timing analysis and timing verification are very well addressed.”

Jochen Rein, SVP Business Unit Software Platform, Vector, stated, “The combination of the NXP CoreRide platform and Vector’s software foundation provides a robust basis for next‑generation zonal architectures. We enable our joint customers to reduce their time- to-market due to a pre-integrated and highly optimized software stack.”

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