Artificial intelligence (AI) is beginning to reshape fleet management beyond conventional telematics that merely track vehicles. In India’s fragmented trucking ecosystem, where cost pressures, ageing fleets and operational inefficiencies remain persistent challenges, AI-led platforms are attempting to shift the industry from reactive monitoring to predictive decision-making. Mumbai-based Taabi Mobility Limited is among the companies advancing this shift, using large-scale data analytics to link driver behaviour, vehicle performance and operating conditions, offering fleets actionable insights aimed at reducing costs, improving safety and optimising asset utilisation.

Generally, most fleet management platforms track location, speed and unauthorised stops, making them mainly descriptive and not prescriptive. Mumbai-based Taabi Mobility Limited is changing the narrative leveraging the computing and predictive power of artificial intelligence (AI).

“Our AI solution adds value by correlating thousands of variables like driver behaviour, road conditions, load, ambient temperature, tyre age etc. and continuously learning in real time. It predicts outcomes. Moreover, traditional reports are static, while AI gets more accurate over time, adapting to different routes. Threshold alerts are not just fixed values. AI detects unusual rates of change and alerts proactively,” explained Chief Executive Officer Pali Tripathi.

Alluding to whether the AI platform only analyses data or also guides operators in real time, she explained that alerts differ by user. “Drivers get in-cabin voice alerts about tyre pressure, fatigue, collision risk etc. Fleet operators receive aggregated, actionable insights across many trucks via a live dashboard with critical exceptions highlighted,” Tripathi said.

She added that the effectiveness of AI relies on high-quality data. The control tower suggests actions like contact drivers, schedule maintenance or recommend coaching but does not fully automate vehicle control. Alert volume is configurable to prevent human fatigue.

She noted that the company’s solution also provides specific corrective actions. “A truck from Delhi to Jaipur showing left-tyre vibration and slow pressure drop triggers an alert for the driver to stop at the next halt. Fleet managers are also notified. The system identifies the issue, potential cause and suggested solution, not just the symptom,” explained Tripathi.

Tripathi contended that the fleet management sector in India is seeing multi-modal transport hubs, digitisation, improved road and waterway connectivity and better warehousing and last-mile efficiency. However, the industry is still not fully organised like in developed countries.

Taabi, she explained, is an operations intelligence platform designed to reduce total operational costs per truck by predicting issues rather than relying on fixed schedules. The system monitors vehicle behaviour, load, road conditions and tyre pressure to flag problems early.

“While fleets focus on fuel cost, tyre health directly impacts safety and performance. Fleet interest in tyre solutions is usually part of a holistic cost-reduction strategy rather than a standalone concern. A 10 percent improvement in tyre life can save crores of rupees for large fleets, making investments in platforms like Taabi worthwhile,” said Tripathi.

Companies in last-mile logistics and cement or steel transporters actively track these metrics through Taabi’s solution.

When asked about collaboration with tyre manufacturers and vehicle OEMs for data sharing, Tripathi indicated that such partnerships are still evolving and not yet fully formalised. She noted that major commercial vehicle OEMs along with tyre manufacturers already collect operational data independently for research and product development.

However, the company’s platform currently prioritises a customer-first approach, focusing on empowering fleet operators with actionable insights. Instead of directly supplying data to OEMs, the system enables fleets to use operational intelligence to hold manufacturers accountable for vehicle performance.

FROM GROUND UP

The company currently serves around 1,300 fleet operators across India. Growth is measured in assets deployed rather than just customers, as a single vehicle may use multiple solutions such as OBD devices, video telematics and fuel monitoring systems. Average deployments are about 272 assets per fleet with ranges from 50 to 4,000 assets.

The company has recorded 130–132 percent year-on-year growth, largely driven by expanding deployments within existing customers.

Nonetheless, Tripathi explained that the primary hurdle for the company was building trust in a completely new category of product. “Since fleets had operated for decades without such technology, convincing operators that the platform could deliver measurable value was difficult. We therefore positioned AI not as a replacement for human judgment but as a tool that enhances decision-making, highlighting hidden operational costs such as tyre wear, vehicle inefficiencies and the financial impact of driver behaviour,” she averred.

Another major challenge was the data ‘chicken-and-egg’ problem. AI systems require large datasets to function accurately, but fleet operators were hesitant to adopt the platform without proof of performance.

Although the company had access to global data, it began collecting India-specific road, load and operational data three to four years before launch to train its models. Early adopters and pilot customers were told transparently that the system would improve as more local data was gathered.

A further complexity involved customising the user interface and experience for different sectors. Construction fleets, buses, trucking companies and enterprise operators such as ambulance services all required different dashboards and operational insights. As a result, persona-based interface design became an important part of product development. When discussing adoption among smaller fleet operators, Tripathi noted that fleets with 5–20 trucks typically adopt the solution through larger enterprises or ecosystem partners.

To improve accessibility, the company offers subscription-based pricing similar to mobile phone plans, avoiding large upfront costs. The base plan provides simple alerts and WhatsApp-style notifications. More advanced features are included in Gold and Platinum plans, which deliver deeper analytics and operational insights.

IMPLEMENTATION

Addressing the challenge of deploying AI-based fleet monitoring on older commercial vehicles, Tripathi noted that a large share of India’s truck and bus fleet is 10–20 years old, meaning many vehicles lack factory-fitted OBD or tyre pressure monitoring systems (TPMS).

“To overcome this, we use a matchbox-sized device that plugs into aftermarket OBD ports typically available on trucks manufactured after 2000. The device captures key operational data such as engine performance, speed, RPM, load conditions and fuel consumption,” she noted.

For older vehicles without such capabilities, additional hardware such as fuel tank sensors are installed to track consumption and detect issues like fuel theft or reverse draining. The system can also monitor gensets and auxiliary equipment, while video telematics can be added when required.

Tripathi explained that this approach can actually make the platform particularly valuable for older fleets, enabling both small and large operators to access AI-driven monitoring and predictive maintenance.

The platform also supports intelligent cameras inside the cabin and facing the road, enhancing driver behaviour monitoring and safety analytics. For tyre monitoring, fleets can use external TPMS units, although these are relatively expensive. As a cost-effective alternative, the system derives proxy performance indicators from OBD data and telematics to estimate tyre health and vehicle performance.

“In minimal deployment scenarios, even a driver’s smartphone can provide basic telematics functions such as GPS tracking, route adherence, geo-fencing and idle detection, enabling gradual adoption of digital fleet management tools,” noted Tripathi.

The platform follows strict data security and privacy standards. All operational data is end-to-end encrypted using AES-256 and stored on cloud infrastructure within India through Microsoft Azure. Fleet data remains private to each operator, meaning one fleet cannot access another’s information.

Internally, only aggregated data is used for model training without exposing raw fleet-level details. Any external data sharing is tightly controlled and compliant with India’s Digital Personal Data Protection framework.

MARKET DEMAND

The company views the retrofit segment as the largest opportunity in India, as most commercial vehicles are older and new truck sales represent only a small share of the total fleet. Its strategy is to democratise access to fleet intelligence by enabling AI-driven monitoring on existing vehicles rather than waiting for fleet modernisation.

“We also see growing relevance in commercial EV fleets, particularly in last-mile delivery networks. Our platform acts as an intelligence layer for mixed fleets transitioning from diesel to electric vehicles, helping operators evaluate return on investment, identify suitable routes for EV deployment and manage operational economics. Vehicle-agnostic solutions such as video telematics can be deployed across cars, vans and EV delivery vehicles,” Tripathi contended.

Rather than relying solely on hardware innovation in tyres or vehicles, the company focuses on AI-driven insights derived from sensor data. “Continuous monitoring allows our system to predict performance issues and recommend interventions. The platform functions as an operational intelligence layer, offering voice-based guidance for drivers, cost-optimisation insights for fleet owners and operational support for fleet managers,” averred Tripathi.

Devices installed in vehicles perform round-the-clock monitoring of engine, fuel, tyre and other operational parameters, delivering predictive alerts and actionable insights. By simplifying complex data into clear recommendations, the AI platform aims to improve fleet efficiency, reduce costs and enable smarter operational decisions.

Comments (0)

ADD COMMENT

Link Copied!

Michelin has partnered with the University of Poitiers, Grenoble Alpes University, Grenoble INP – UGA and the CNRS to launch I-TireLab, a joint laboratory combining data and modelling to pursue advances in tyres, tyre manufacturing and flexible composites. The project carries a total investment of roughly EUR 4.5 million over four years and is intended to close the gap between academic research and industrial challenges.

The laboratory pairs Michelin's expertise in tyre simulation and modelling, materials and industrial processes with the modelling, system state estimation and control methodology strengths of the Laboratory of Computer Science and Automatic Control for Systems at Poitiers and the GIPSA-lab, which unites UGA, CNRS and Grenoble INP – UGA. Though the partnership has operated for several years, I-TireLab gives it a long-term framework aimed at turning data into knowledge, decisions and actions.

The teams combine data analysis and modelling to represent and predict the behaviour of tyres, processes and materials, then test the relevance and limits of those models through data and experimentation. Four research themes support safer, higher-performing mobility, less resource-intensive manufacturing and new applications for flexible composites.

The first theme targets a clearer view of tyre condition on the road, including real-time estimates of wear and grip using existing on-board sensors without specialised equipment. The second feeds that information into vehicle control systems, optimising braking based on tyre status and grip potential to enhance stability and efficiency. The third addresses rubber manufacturing, developing simulation and control tools to anticipate equipment operation and fine-tune settings while maintaining consistent quality and limiting waste and energy use. The fourth explores how flexible products can influence air and water flows around objects through control laws that alter component shapes.

Michelin contributes product-usage understanding, data and experimental and industrial resources, while the academic laboratories supply theoretical and methodological expertise for designing and validating new approaches. The collaboration also helps train young researchers at the interface of fundamental research, experimentation and industrial needs, with access to demonstrators and partner-site tests for near-real-world assessment.

Planned applications include supporting Michelin Touch Intelligence, the tyre digital twin unveiled in May 2026 that estimates pressure, wear, load and grip in real time without extra sensors across all brands and models. Research on certain flexible composites could also inform Wisamo, Michelin's inflatable, retractable automated wingsail, whose first unit is in delivery and which uses wind to boost ship propulsion and cut fuel consumption.

Philippe Jacquin, Michelin General Manager & Director of Research and Development, said, “I-TireLab will make it possible to turn science into real-world innovations, from tyres and tyre manufacturing to tyre-vehicle interactions. Michelin Touch Intelligence, the tyre digital twin is one recent illustration of what that means in practice: when we know more about the tyre’s status and grip potential, we can enable vehicle adjustments and optimisation.”

Guillaume Mercère, I-TireLab Director; John Martinez-Molina, I-TireLab Co-Director and Thibault Dairay, I-TireLab Co-Director, said in a joint statement: "I-TireLab brings together researchers, engineers and young scientists to make mobility safer, improve our control of tyre manufacturing, and explore new possibilities for flexible materials. By drawing on fundamental research, experimentation and industrial needs, we are developing new methods, training talents and preparing the innovations of the future, together.”

Mehdi Gmar, CNRS Deputy CEO for Innovation, said, “I-TireLab once again demonstrates that the expertise and knowledge developed in academic research laboratories – in this case, at GIPSA-lab in modelling and control of complex systems – have industrial applications. This is now the case with Michelin across very different areas: tyres on the road, rubber manufacturing and flexible materials supporting safer, more resource-efficient mobility.”

Comments (0)

ADD COMMENT

Link Copied!

Swarnakaruna Princeton Rubber Industries has built capacity to recycle about 96,000 end-of-life tyres annually after government-backed financing helped the Visakhapatnam company transition from processing buffing waste to recycling whole tyres. The recycler is now targeting larger industrial buyers while exploring tyre imports to lower raw-material costs.

India’s push to formalise its end-of-life tyre recycling ecosystem is creating room for smaller recyclers to scale, but access to capital, machinery reliability, raw-material costs and the economics of producing higher-grade crumb rubber remain significant constraints.

Visakhapatnam-based Swarnakaruna Princeton Rubber Industries Private Limited offers a case in point. The company has expanded from a small operation processing buffing powder to a whole-tyre recycling business capable of producing around 300–400 tonnes of crumb rubber a month following financial support channelled through IFCI Venture Capital under a government-backed programme for Scheduled Caste entrepreneurs.

The business traces its roots to 2014, when Managing Director N Swarnalatha established K.S. Princeton Rubber Industries after approaching the District Industries Centre in Visakhapatnam with plans to become an entrepreneur.

The original operation had a single grinder and relied on buffing powder as its principal feedstock because it lacked the equipment required to process complete end-of-life tyres.

“The company started in 2014, but the setup was very minimal. We had just one grinder and were not capable of recycling a whole tyre, so buffing powder was our raw material,” said Swarnakaruna Princeton Rubber Industries Chief Executive Officer Ashish Kumar Isukapati.

That model began changing in 2018 when the company sought funding from IFCI Venture Capital Limited. The proprietorship was subsequently converted into a private limited company as part of the process of securing the investment. Funding was eventually released in stages, with commercial production from the expanded facility beginning in August 2024.

According to Isukapati, the project received about INR 50 million from IFCI Venture Capital, alongside a promoter contribution of INR 17.1 million. The overall project cost was approximately INR 67.21 million.

The money was deployed largely towards machinery and rebuilding and expanding the existing manufacturing premises.

Isukapati said the financing was particularly significant because conventional access to growth capital can prove difficult for first-generation entrepreneurs.

TYRES TO CRUMB

The expanded operation can process roughly 8,000 end-of-life tyres each month, equivalent to around 96,000 tyres annually, according to Isukapati. At the upper end of production, the facility can manufacture around 400 tonnes of crumb rubber a month, while recovered steel accounts for roughly 25 percent of output by weight or around 100 tonnes at that production level.

The company currently sells entirely into the domestic market, with Kerala representing its largest destination. It also supplies TVS Sundaram Industries in Chennai.

However, the economics vary considerably according to crumb size and end application.

More than 70 percent of the company’s current crumb-rubber production goes to non-tyre applications, particularly rubber-mat manufacturers in Kerala. These customers typically consume 20 and 24 mesh material. TVS Sundaram Industries takes roughly 60–80 tonnes a month, with the company supplying 30-mesh crumb rubber.

Tyre-related customers typically require finer grades such as 40, 60 and 80 mesh crumb rubber. The company has pulverising equipment capable of producing material in those ranges, but finer grinding lowers throughput and changes the economics of the operation.

“We are capable of manufacturing the higher meshes, but the overall output comes down. We have to balance which mesh we manufacture against the quantity we can produce because crumb rubber itself is a relatively low-priced product. The way to generate sustainable revenue is through volume,” Isukapati said.

That volume-quality equation has become particularly important as the recycler seeks to tap larger customers closer to its Visakhapatnam plant.

One of its main targets is HINCOL, which Isukapati said operates a facility locally and requires around 500 tonnes of crumb rubber a month. The company has so far been unable to fully address that opportunity because of the combination of volume, quality specifications and tender pricing.

Isukapati sees similar opportunities with buyers across the eastern and southern tyre and rubber manufacturing belt. He estimates that potential demand within roughly 300 kilometres of its operation could exceed 1,000 tonnes a month.

The challenge is converting that proximity into profitable sales.

PORT OPPORTUNITY

The company currently sources a significant portion of its tyres through Andhra Pradesh State Road Transport Corporation auctions. And the company is also seeking a licence to import end-of-life tyres, a move it believes could allow it to leverage its proximity to Visakhapatnam port and reduce feedstock costs.

“We are trying to capitalise on Visakhapatnam port and have applied for an import licence. If that works out, we could spend less on raw material, which would give us an advantage in offering a more competitive price,” Isukapati said.

The company’s expansion has not been without setbacks. Location presents a significant constraint. The facility operates on a plot of about 980 square yards, where incoming tyres, finished crumb rubber and recovered steel all have to be stored and managed. Expanding towards the 500-tonne monthly volumes sought by larger customers could therefore require the company to address its space limitations.

Technical support and spare-part availability are also more difficult in Visakhapatnam than in established manufacturing clusters, Isukapati said.

BIGGER CHALLENGE

Swarnakaruna does not currently operate a dedicated research and development department. Product development and process adjustments are handled by its production manager and technical staff, while third-party laboratories are occasionally used when customers require test reports.

Beyond the company’s own expansion, Isukapati sees feedstock pricing as one of the biggest problems confronting India’s mechanical tyre recyclers.

Waste-tyre prices can rise when pyrolysis operators increase production, but crumb-rubber producers cannot necessarily pass those higher costs to customers because buyers have multiple competing suppliers.

He also called for greater policy attention to the procurement and channelisation of waste tyres, arguing that mechanical recyclers do not necessarily receive a commercial advantage for converting end-of-life tyres into reusable rubber products.

His comments come as India’s tyre-recycling ecosystem adjusts to extended producer responsibility requirements and increasing competition for waste-tyre feedstock.

For the tyre recycler, the next phase will therefore be less about simply adding equipment and more about achieving scale economically. The company is seeking cheaper feedstock, higher production, access to larger nearby customers and potentially a more formal research and development structure.

Recovered steel also remains important to the economics of the operation. Despite the constraints, he sees a sizeable addressable market around the company’s Visakhapatnam base.

“The opportunity is absolutely there. If we can get the right balance between the mesh we manufacture, the quantity we produce and the price, there is a huge opportunity out there,” Isukapati said.

Comments (0)

ADD COMMENT

Link Copied!

DUNLOP (company name: Sumitomo Rubber Industries) has confirmed that its proprietary SENSING CORE technology has been adopted for medium-duty truck models. The system, designed to detect the conditions of tyres, vehicles and road surfaces, is fitted to Isuzu Motors' FORWARD medium-duty trucks with a gross vehicle weight exceeding 14.5 metric tonnes, which come standard with the Wheel Detachment Prediction Detection System, one of the functions offered by SENSING CORE.

SENSING CORE is a software technology built on expertise gained from the Deflation Warning System, a tyre pressure warning system. It analyses wheel speed data generated by tyre rotation together with controller area network data transmitted through the vehicle's control system, allowing it to detect various tyre and road conditions, including tyre pressure, wear, load and signs of potential wheel detachment. The Wheel Detachment Prediction Detection System in Isuzu's FORWARD models detects loosening of wheel nuts while the vehicle is in motion, alerting the driver through a warning message and buzzer if an abnormality is found.

This capability complements conventional inspections and driver experience and is expected to play a significant role in preventing wheel separation accidents. Isuzu's FORWARD is a medium-duty truck with a broad lineup designed to meet diverse logistics industry needs, and such trucks are widely used in local delivery, long-haul transport and building and construction operations, serving as a vital means of transportation.

Operated across urban areas and major highways, wheel detachment accidents involving these trucks could cause serious harm to third parties such as pedestrians and cyclists, driving growing societal demand for improved safety. Preventing such accidents requires fundamental inspection and maintenance measures, yet drivers find it difficult to detect loosening wheel nuts while driving, making early-detection technologies essential. The provision of the Wheel Detachment Prediction Detection System to medium-duty trucks enables early detection of signs of vehicle malfunctions and contributes to further improving safety and preventing wheel detachment accidents.

Comments (0)

ADD COMMENT

Link Copied!

SYMX.AI, a developer of artificial intelligence technology for mobile industrial equipment, has raised USD 6 million in Series A financing led by Ascent Capital Partners and agreed a global technology and commercial partnership with Yokohama Off-Highway Tires.

The Canadian company develops software and hardware for mining, construction and forestry operations. Its platform provides connectivity in areas without network coverage, integrates data from equipment made by different manufacturers and supports fleet optimisation.

Its products cover dispatch, fleet management, enterprise asset management and tyre life management, as well as equipment health, fuel consumption, haul road intelligence, inventory and operator performance. The company also holds patents covering its internet of things and AI technologies, including a patent for its “Greenhouse Gas Emissions Data Collection and Cross-Validation System”, granted in 2026.

SYMX.AI has also launched an AI-powered inspection platform and a chatbot for industrial operations.

“Physical AI has been struggling in mining for simple reasons. The machines are mobile, mixed-fleet data is vendor-locked, and most of the industry has limited to no network coverage. Intelligence needs a body and a nervous system before we deploy a model. Even today, assembling that foundation takes seven or eight vendors and up to twelve months. We deliver it in a week. We built the hardware and the connectivity first, which is why our AI layer delivers real results. I am glad that capital is finally flowing to atoms again, and mining will finally get what it has long deserved,” said Ash Agarwal, CEO of SYMX.AI.

Technology tested in mining operations

SYMX.AI said it had validated its technology through projects across the mining value chain. At Glencore's Onaping Depth project in Ontario, Canada, the company demonstrated battery monitoring, short-interval control and fleet optimisation for battery-electric vehicles.

“The problem SYMX.AI solves is foundational,” said Peter Xavier, Chief Operating Officer of Canada Metals, a Glencore company. “Connectivity and cross-OEM data integration at the point of work are infrastructure gaps the mining industry has struggled with for decades, but SYMX.AI changes the paradigm. Our proof-of-concept validation of the SYMX.AI platform on our OEM BEV equipment successfully supports underground short-interval control, battery monitoring and fleet optimization. This level of integration and insight is exactly what the industry needs to move forward.”

Global partnership with Yokohama

Under the partnership, Yokohama Off-Highway Tires will offer the integrated hardware and software platform to customers through its international commercial network. SYMX.AI will supply the internet of things hardware, connectivity, cloud platform and intelligence capabilities.

Customers will be able to adopt the technology as a standalone tyre intelligence solution or as part of a broader fleet optimisation platform.

“The tyre technology market is crowded with TPMS providers, but most systems monitor pressure and temperature while offering little insight beyond those measurements. Operators are asking a more important question: can the same system help us increase production, protect valuable assets such as tires and reduce fuel consumption? SYMX.AI has built a complete platform that addresses this market need by connecting tire condition with equipment performance, haul road conditions and operator behavior. This helps sites reduce costs, extend tire life and improve overall fleet performance,” said Loïc Ravasio, President of Yokohama Off-Highway Tires. “By working with SYMX.AI and offering flexible business models, Yokohama OTR is becoming a true digital partner to the industry, helping customers optimize their operations.”

Expansion and investment

SYMX.AI is expanding its product range with an AI-driven dispatch and fleet management system and an enterprise asset management platform based on live machine sensor data and fault codes.

The asset management system combines equipment health monitoring, diagnostic alarm management, oil analysis and work order management. The company says the system is designed to reduce reliance on fixed maintenance schedules and manual data entry.

Its products integrate with AVEVA Connect, SAP, Oracle and existing data historians, allowing operators to add the technology without replacing their existing systems.

The company said it supported open-pit and underground operations in Kazakhstan, the US, Mexico, Europe and Asia.

“We have watched this team for three years demonstrating grit, perseverance, and commitment. They build things that work in places most software never reaches, and the customers keep renewing worldwide. That is rare in this industry. The comprehensive IoT, connectivity, and AI app layer is deployed at difficult sites, and I’m glad that the market is finally catching up,” said Jonathan Loeffler, Co-Founder and Managing Partner of Ascent Capital Partners.

The financing will support international deployment, development of the AI platform and a broader range of wireless communication products, SYMX.AI said.

Comments (0)

ADD COMMENT

Link Copied!