Singapore-headquartered angel investment platform ThinKuvate has announced the first close of its India fund at INR 250 million. The investment comes within four months of the formal launch of the ThinKuvate India Fund — I.

The firm has made investments in four startups – Rosh.ai, Zippee, Pantherun, and NymbleUp.

Rosh.ai was founded in 2021 by Roshy John and Rajaram Moorthy. It specialises in autonomous vehicle technology, providing solutions for the automotive, seaport, and mining industries. The company has raised $1 million in Pre-Series A led by EV2 Ventures, with participation from Caret Capital and ThinKuvate.

Zippee was founded by Madhav Kasturia in 2021 and offers same-day delivery for more than 100 (D2C) brands. Zippee is scaling its operations in metro cities and expanding its brand partnership.

Founded in 2019 by Srinivas Shekar, Pantherun is a cybersecurity company specialising in advanced data protection solutions. The company has raised a bridge round led by QuickHeal Family Office and SIDBI Ventures, with participation from 8X, PiperSerica, and ThinKuvate.

NymbleUp.ai was founded in 2019 by Yogesh Bhatt & Manish Thakur. It has secured pre-series A  led by Chandigarh Angels, IVY Cap, and ThinKuvate. It provides AI-driven predictive workforce management solutions for QSRs and retail chains; forecasting demand across all sales channels at 15-minute intervals. 

ThinKuvate plans to invest in early-stage startups from seed to Series A, focusing on companies leveraging technology at the forefront.

Ghanshyam Ahuja, Managing Partner, ThinKuvate said, “We have been investing in Indian startups and saw the potential growth opportunities. That led us to launch an India-focused fund, we have reached the first milestone in little over 100 days. This validates our thesis on the next-gen innovations taking place in India, which have a global appeal.”

ThinKuvate continues to raise its target corpus, the fund plans to invest in 30 – 40 startups with an average investment size of INR 15 million to INR 40 million. The fund has also attracted top tier general partners globally, to manage the deal flow, due diligence, and overall portfolio management. More than 50 percent of investors in the fund are NRIs from various countries, top of them being Singapore, Australia, the USA, the UK, and Indonesia.

Mayank Jain, CEO, ThinKuvate, says, “We have built capabilities within our team to provide support and help to startups scale faster. The profile of limited partners, who are working professionals with senior roles in large corporates, would be a huge differentiator for the companies we back. Our vast network will not only bring in quality capital but provide access to the founders to accelerate their growth journey post funding from ThinKuvate. As we continue to raise the target corpus, we have already built a healthy deal flow and we are confident that with this fund, we will be able to build a strong portfolio and generate stellar returns for our investors.”

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Horse Powertrain, a leading supplier of powertrain solutions, has launched the V20 engine through its Aurobay Technologies division with production already underway at its Skovde, Sweden, manufacturing facility.

The V20 engine aims to assist automakers in meeting emission regulations for 2026 and 2027 with units destined for customers in Europe, the US and Asia. The 2.0-litre, 4-cylinder engine features a single architecture offered in two variants: a 400-volt plug-in hybrid and a 48-volt mild hybrid. The plug-in version provides a reduction in fuel consumption of seven per cent compared to the predecessor.

The platform design intends to reduce material costs. Hardware for the plug-in variant includes a crankshaft-mounted starter-generator, a mechanical water pump, and a re-routed cooling system. Additional updates include a multi-injection fuel system, an engine management system, and an air induction system.

Ingo Scholten, Managing Director, Aurobay Technologies Sweden and Deputy CTO of Horse Powertrain, said, “Designing one engine to meet three different regulatory regimes is harder than designing three separate engines. As the regulatory map is fragmenting, one engine that meets all three sets of rules delivers greater value to our customers, ensuring we can offer greater economies of scale. Pulling that off requires serious engineering. Further, the Skovde team also successfully changed production lines while keeping current production running.”

The Skovde plant integrated a final assembly line with the base assembly line to improve material flow. This transition occurred during ongoing operations. Output is scheduled to increase through 2026 and 2027 to meet demand.

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AEye, Inc. and MoveAWheeL have signed a Memorandum of Understanding to explore the integration of their sensing technologies for use in Advanced Driver Assistance Systems (ADAS) and autonomous driving applications.

The partnership aims to combine AEye’s lidar perception with MoveAWheeL’s road-surface sensing to assist vehicles in interpreting surroundings and road conditions.

The collaboration will evaluate the pairing of AEye’s Apollo LiDAR sensor with MoveAWheeL’s friction-coefficient prediction technology. Apollo is a 1550-nanometer LiDAR sensor capable of detecting objects at distances of up to one kilometre. MoveAWheeL’s sensor uses acoustic sensing to estimate the friction of road surfaces, providing data to inform decisions regarding acceleration, braking and stability control.

Matt Fisch, Chairman and CEO of AEye, said, “Physical AI depends on giving machines the ability to accurately perceive and understand the real world. Apollo was designed to deliver long-range, real-time 3D perception that helps systems see farther and react earlier in complex environments. By exploring the integration of Apollo with MoveAWheeL’s road-surface intelligence, we have the opportunity to create an even deeper understanding of the driving environment, particularly in the adverse conditions where advanced safety systems are needed most.”

Dr. Min-Hyun Kim, Founder and CEO, MoveAWheeL, said, “While LiDAR provides the ‘eyes’ for a vehicle to see obstacles, MoveAWheeL provides the ‘tactile sense’ to feel the road. By integrating our Physical AI with AEye’s long-range perception, we are creating a complete safety stack that remains robust even in the most treacherous weather conditions.”

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L&T Technology Services (LTTS), a leading ER&D sevices company, has inaugurated its first Engineering Intelligence Centre of Excellence (EI CoE) in Munich, Germany. The facility marks a step in the company's Engineering Intelligence (EI) strategy, which focuses on embedding AI across the engineering lifecycle to support intelligent products, autonomous operations and manufacturing systems.

The centre aims to assist global enterprises in transitioning from AI experimentation to industrial transformation by combining domain engineering expertise with technologies such as GenAI, Agentic AI, multimodal AI, Physical AI and edge intelligence. LTTS states that it has filed over 237 patents in AI and GenAI during FY2026.

Located within a technology ecosystem, the Munich EI CoE will function as a collaborative hub for clients in the mobility, industrial products, sustainability and technology sectors. Its work will focus on: Applied AI solutions, Intelligent manufacturing, Software-defined products, Predictive operations and Connected engineering ecosystems.

At present, LTTS serves more than 60 clients in Europe with a team of over 4,500 engineers. The new centre is intended to improve local collaboration with clients, partners and academic institutions, facilitating outcome-driven innovation.

Amit Chadha, Chief Executive Officer & Managing Director, L&T Technology Services, said, “LTTS’ first EI Centre of Excellence in our Munich design centre is a milestone as it brings our deep-tech and EI-based solutions closer to the clients’ R&D hubs across the region. The centre will act as a focal point for innovation, R&D and new product development, redefining how products, platforms and manufacturing are engineered and optimised in the AI era.”

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European automaker Stellantis has announced a strategic initiative with Accenture to deploy artificial intelligence (AI)-enabled digital twin capabilities across its global manufacturing network using Nvidia technologies. The project focuses on creating virtual manufacturing environments powered by real-time data and physical AI.

The collaboration integrates Stellantis's automotive infrastructure, Accenture’s digital manufacturing engineering and Nvidia’s accelerated computing platforms and Omniverse libraries.

The system uses virtual factory replicas to validate manufacturing processes prior to physical installation, track metrics for quality control and conduct predictive monitoring.

Initial testing and deployment of the digital twin infrastructure are scheduled to begin with pilot programmes in North America in 2026. The long-term objective is to evaluate scalability across the carmaker's international plant footprint to establish a predictive manufacturing model.

Francesco Ciancia, Head of Manufacturing, Stellantis, said, “We are laying the foundation for the next generation of manufacturing at Stellantis. By combining digital twins, AI and advanced simulation, we are rethinking how we design, operate and continuously improve our production systems. This initiative is designed to work hand in hand with our teams, enhancing their ability to anticipate issues, enabling faster decisions and continuous improvement. Together with Accenture and NVIDIA, we are exploring new ways to drive more scalable and intelligent operations.”

Tracey Countryman, Supply Chain and Engineering Global Lead, Accenture, added, “The opportunity in manufacturing today is to scale AI across complex industrial operations in ways that deliver measurable business value. By partnering with Accenture and harnessing Nvidia’s compute and simulation technologies, Stellantis is positioned to accelerate manufacturing reinvention and lead the industry into a new era of intelligent, high-performance operations.”

The computational framework is built to enable closed-loop optimisation, a process where physical assembly lines and virtual systems continuously exchange data to improve performance. The architecture supports automated throughput adjustment, maintenance scheduling and software-defined factory operations.

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