Tensor Planet

03/18/2026

𝗗𝗮𝘆 𝟭 𝗮𝘁 Technology & Maintenance Council (TMC) of American Trucking Associations, Inc. 𝗘𝘃𝗲𝗻𝘁 𝗶𝗻 𝗡𝗮𝘀𝗵𝘃𝗶𝗹𝗹𝗲, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗲𝗻𝗲𝗿𝗴𝘆 𝗶𝘀 𝗶𝗻𝗰𝗿𝗲𝗱𝗶𝗯𝗹𝗲! 🚛

The predictive maintenance session was absolutely packed- not even standing room! It's clear this is top priority for fleets across the industry.

Love seeing the trucking and tech community come together to shape the future of fleet maintenance.

If you are in Nashville attending TMC, make sure you hit up (GK) Ganes Kesari !

03/06/2026

🚛 41% fewer repairs. $18,000 saved in just 10 weeks.
Troiano Waste Services is driving results with Tensor Planet’s AI-powered predictive maintenance, seamlessly integrated into daily fleet operations.

By following AI-driven recommendations, their technicians prevent 4+ service disruptions every week, reclaim valuable shop time, and keep trucks on the road—without adding new tools or changing workflows.

“For the shop, the biggest win was how simple this was for the technicians. They didn’t need to learn a new tool or change their routine.”
– Scott Lane, Fleet Manager, Troiano Waste Services

👉Read the case study here:https://tensorplanet.com/wp-content/uploads/2025/11/Tensor-Planet-Customer-Case-Study-short-version.pdf

03/05/2026

Stop costly breakdowns before they happen!

Construction fleets face extreme wear and tear, but AI-powered predictive maintenance is changing the game.
🔧 Tensor Planet’s AI Fleet Maintenance continuously monitors vehicle health, detects early warning signs weeks in advance, and guides teams with clear, actionable recommendations.
✅ Reduce unplanned repair costs
✅ Extend vehicle lifespan
✅ Boost uptime & safety
✅ Achieve measurable ROI every quarter

In an industry where downtime means lost revenue and delayed projects, predictive maintenance isn’t just smart—it’s essential.

👉 Read more about how AI is revolutionizing fleet reliability: https://tensorplanet.com/fleet-breakdowns-in-construction-how-ai-powered-maintenance-software-reduces-fleet-downtime-costs/

Learn how AI powered maintenance software and telematics data help construction fleets prevent breakdowns, reduce fleet downtime costs, and shift from reactive repairs to predictive maintenance.

03/02/2026

🚧 Downtime is the most expensive risk in heavy civil construction.

One paving machine sitting idle can cost contractors $112,000 per day. For the top 500 U.S. heavy civil contractors, that adds up to $30 billion in annual losses.
Reactive maintenance simply can’t keep up with stakes this high.

At Tensor Planet, we use AI and your existing telematics data to help fleets stay ahead of failure:
✅ Spot high-risk machines before they disrupt jobs
✅ Shift from emergency repairs to planned maintenance
✅ Protect project timelines and margins by reducing downtime

When every day of downtime costs six figures, waiting for failure isn’t just risky—it’s the most expensive strategy.

👉 Discover how our AI Fleet Maintenance solution keeps your equipment running: https://tensorplanet.com/

02/27/2026

🛠️𝟒𝟏% 𝐟𝐞𝐰𝐞𝐫 𝐫𝐞𝐩𝐚𝐢𝐫𝐬 𝐚𝐧𝐝 $𝟏𝟖,𝟎𝟎𝟎 𝐬𝐚𝐯𝐞𝐝 𝐢𝐧 𝟏𝟎 𝐰𝐞𝐞𝐤𝐬

Troiano Waste Services is an active customer, running Tensor Planet’s AI-powered predictive maintenance as part of daily fleet operations.

Their technicians rely on AI recommendations as part of normal shop workflows, preventing 4+ service disruptions per week and freeing up critical technician time without adding tools or process changes.

"For the shop, the biggest win was how simple this was for the technicians. They didn’t need to learn a new tool or change their routine."
– Scott Lane, Fleet Manager, Troiano Waste Services



👉Read the case study here:https://tensorplanet.com/wp-content/uploads/2025/11/Tensor-Planet-Customer-Case-Study-short-version.pdf

02/25/2026

🚛 Scheduled maintenance alone does not prevent fleet breakdowns.

In waste, construction, and freight operations, components rarely fail without warning. Performance drifts gradually as vehicles operate under real-world load and stress. Yet most fleets still rely on fixed time or mileage intervals that do not reflect how each asset is actually used.

The earliest signs of trouble often show up as small shifts in temperature, fuel efficiency, vibration, or pressure. On their own, these changes seem minor. Over time, they compound.

Predictive maintenance brings those signals together.

By analyzing time-series telematics data, AI detects gradual performance drift and estimates failure risk before a roadside event occurs. Instead of waiting for fault codes, fleets can prioritize intervention based on measurable probability.

The outcome is fewer emergency repairs, better service timing, and longer asset life driven by real operational behavior.

👉 Read the full blog:
https://tensorplanet.com/why-scheduled-maintenance-alone-doesnt-prevent-fleet-breakdowns/

Scheduled fleet maintenance cannot fully prevent fleet breakdowns. Learn how predictive maintenance using AI-powered maintenance software and telematics time-series data enables early signal detection, risk-based intervention, and fleet breakdown prevention.

02/23/2026

🚧 One down paving machine can cost a contractor $112,000 per day.

According to GearFlow, equipment downtime is the ultimate risk in heavy civil construction. When a machine goes down, the job often goes down with it.

For the top 500 U.S. heavy civil contractors, these losses can add up to $30 billion per year.

The scale of the problem is staggering. This is why it feels impossible to get ahead using reactive maintenance.

At Tensor Planet, we help construction fleets detect failure risk early using AI and existing telematics data, so teams can:
✅ Identify high-risk machines before jobs are disrupted
✅ Shift work from emergency fixes to planned maintenance
✅ Reduce downtime that directly hits project timelines and margins

When downtime costs six figures per day, waiting for failure is the most expensive strategy.



👉 Check out our AI Fleet Maintenance product: https://tensorplanet.com/

02/16/2026

🚛 Unplanned downtime is costing fleets more than they realize.

According to Michelin, every hour of unplanned downtime costs commercial fleets an average of $760 per day. Over time, this can drive operating costs up by as much as 20% due to repairs, labor, missed deliveries, rerouting, and excess fuel use.

The real issue is not that breakdowns happen. It is that fleets often see them only when it is already too late.

At Tensor Planet, we help fleets spot failure risk weeks in advance using AI and existing telematics data, so teams can:
✅ Detect high-risk vehicles before downtime hits
✅ Shift repairs from emergency to planned service
✅ Lower operating costs driven by reactive maintenance

When downtime costs this much, reacting late is the most expensive strategy.



👉 Check out our AI Fleet Maintenance product:

AI-powered predictive maintenance helps fleets cut costs, prevent breakdowns, and extend vehicle life. Discover Tensor Planet’s ROI-driven solution.

02/13/2026

📢 𝐔𝐩𝐜𝐨𝐦𝐢𝐧𝐠 𝐖𝐞𝐛𝐢𝐧𝐚𝐫: 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐅𝐥𝐞𝐞𝐭 𝐌𝐚𝐢𝐧𝐭𝐞𝐧𝐚𝐧𝐜𝐞: 𝐇𝐨𝐰 𝐂𝐨𝐦𝐦𝐞𝐫𝐜𝐢𝐚𝐥 𝐅𝐥𝐞𝐞𝐭𝐬 𝐑𝐞𝐝𝐮𝐜𝐞 𝐃𝐨𝐰𝐧𝐭𝐢𝐦𝐞 𝐁𝐞𝐟𝐨𝐫𝐞 𝐈𝐭 𝐃𝐢𝐬𝐫𝐮𝐩𝐭𝐬 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬

𝘿𝙖𝙩𝙚: February 18, 2026
𝙏𝙞𝙢𝙚: 11:00 AM EST
𝘿𝙪𝙧𝙖𝙩𝙞𝙤𝙣: 30 minutes

🎙️ 𝙎𝙥𝙚𝙖𝙠𝙚𝙧: Ganes Kesari, Founder & CEO, Tensor Planet
TEDx Speaker | MIT Sloan Columnist | AI Fleet Expert

✅ 𝙒𝙝𝙤 𝙎𝙝𝙤𝙪𝙡𝙙 𝘼𝙩𝙩𝙚𝙣𝙙:
Fleet Operations, Safety, and Maintenance leaders in freight & logistics, construction, or waste industry with 50+ vehicles

🚛 𝙒𝙝𝙖𝙩 𝙔𝙤𝙪’𝙡𝙡 𝙇𝙚𝙖𝙧𝙣:
• The specific failure signals fleets miss 2–6 weeks before breakdowns
• Why PM schedules surface issues too late, even when followed correctly
• How to prioritize vehicles when technician bandwidth is tight
• What changes when planning is based on risk, not mileage

🎁 𝙎𝙥𝙚𝙘𝙞𝙖𝙡 𝙊𝙛𝙛𝙚𝙧:
First 25 fleet registrations receive a complimentary AI-based fleet risk analysis, including your top-risk vehicles and estimated savings.

𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐧𝐨𝐰 𝐢𝐟 𝐮𝐧𝐩𝐥𝐚𝐧𝐧𝐞𝐝 𝐝𝐨𝐰𝐧𝐭𝐢𝐦𝐞 𝐢𝐬 𝐚 𝐩𝐫𝐨𝐛𝐥𝐞𝐦 𝐲𝐨𝐮’𝐫𝐞 𝐚𝐜𝐭𝐢𝐯𝐞𝐥𝐲 𝐭𝐫𝐲𝐢𝐧𝐠 𝐭𝐨 𝐬𝐨𝐥𝐯𝐞.
👉 https://tensorplanet.com/webinar/

02/11/2026

🚛🔋 Overnight battery drain is one of the most frustrating and disruptive failure modes in fleet operations.

Vehicles often park at the end of the day appearing healthy, only to refuse to start the next morning. These no-start events are rarely random. They build up quietly through parasitic electrical draw, weak batteries masked during daytime operation, and rising electrical loads from onboard systems.

Voltage decay analytics changes this. By analyzing telematics and time-series operational data like resting voltage after shutdown, overnight decay rates, weekend discharge patterns, and recovery behavior, AI can flag battery risk well before a morning no-start occurs.

The result: fewer jump-starts and tows, root causes addressed during planned service, and predictable morning readiness across waste, construction, and freight fleets.

👉 Learn how voltage decay analytics prevents overnight no-start events:
https://tensorplanet.com/battery-drain-overnight-how-voltage-decay-analytics-prevents-no-start-events-in-fleet-operations/

Learn how AI-powered voltage decay analytics detects parasitic draw, weak batteries, and rising electrical loads before they cause costly no-start events in fleet operations.