When farm challenges grow, smart tools need to grow with them.
Updated
November 27, 2025 3:26 PM

A drone spraying water over an agricultural field. PHOTO: FREEPIK
Farms today are under pressure. Fields are getting bigger, workers are harder to find and many jobs still rely on long hours of manual labor. XAG’s new P150 Max agricultural drone is designed for exactly this reality. Instead of replacing farmers, it takes over the heavy, repetitive fieldwork that slows them down, making farm operations more efficient and more precise.
The P150 Max is built around one simple idea: a single machine that can handle multiple farming tasks. Most farm drones focus only on spraying or mapping, but this one is fully modular. With a quick switch of attachments, it can spray crops, spread seeds or fertilizer, map fields or transport supplies. This flexibility helps farmers keep up with changing tasks throughout the day without needing different machines, improving both productivity and cost-efficiency.
A key challenge in agriculture is that fields are rarely smooth or predictable. Tractors can get stuck, smaller drones can’t carry much and some areas—like orchards or hilly plots—are simply hard to reach. The P150 Max fills that gap with an 80-kilogram payload and fast flight speed, letting it cover more ground per trip. Fewer takeoffs mean less downtime and more work completed before weather or daylight cuts operations short.
When it’s time to spray, the drone uses a smart spraying system that allows farmers to adjust droplet size based on the crop’s needs. This matters because precise spraying reduces waste and improves targeting. With an output of up to 46 liters per minute, the drone can serve both large open fields and dense orchards where consistent coverage is traditionally difficult.
The spreading system applies the same logic. Instead of dropping seeds or fertilizer unevenly, the vertical mechanism spreads material smoothly and resists wind drift. This ensures uniform application across irregular or hard-to-reach land—an ongoing challenge for modern farms aiming for higher yield and better resource use.
Another everyday issue for farmers is understanding and surveying the land before working on it. The P150 Max helps here with a built-in mapping tool that covers up to 20 hectares per flight and instantly converts the images into detailed maps. With AI detecting obstacles like trees or irrigation lines, the drone can plan safe and efficient autonomous routes, reducing manual planning time.
Beyond spraying and spreading, the drone can transport tools, produce and farm supplies using a sling attachment. This is particularly helpful after heavy rain, when vehicles cannot easily move across muddy or flooded fields.
Under all these functions is XAG’s upgraded flight control system, which provides centimeter-level accuracy even when network signals are weak. Integrated sensors—including 4D radar and a wide-angle camera—help the drone recognize hazards such as poles and wires. Farmers can manage all operations through the XAG One app or a handheld controller, both of which automatically generate the best route based on field shape and terrain.
Since long field days require long operating hours, the fast-charging battery system can recharge in about seven minutes using a dedicated kit. This supports continuous drone use throughout the day with minimal interruptions.
After years of testing, the XAG P150 Max is essentially an effort to make practical, scalable farm automation more accessible. By combining spraying, spreading, mapping and transport into one heavy-duty platform, it offers a way to ease labor shortages while keeping operations efficient and sustainable. Instead of focusing on one task, the drone aims to take over the time-consuming physical work so farmers can focus on decisions, planning and crop management.
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Examining the shift from fast answers to verified intelligence in enterprise AI.
Updated
November 28, 2025 4:18 PM

Startup employee reviewing business metrics on an AI-powered dashboard. PHOTO: FREEPIK
Neuron7.ai, a company that builds AI systems to help service teams resolve technical issues faster, has launched Neuro. It is a new kind of AI agent built for environments where accuracy matters more than speed. From manufacturing floors to hospital equipment rooms, Neuro is designed for situations where a wrong answer can halt operations.
What sets Neuro apart is its focus on reliability. Instead of relying solely on large language models that often produce confident but inaccurate responses, Neuro combines deterministic AI — which draws on verified, trusted data — with autonomous reasoning for more complex cases. This hybrid design helps the system provide context-aware resolutions without inventing answers or “hallucinating”, a common issue that has made many enterprises cautious about adopting agentic AI.
“Enterprise adoption of agentic AI has stalled despite massive vendor investment. Gartner predicts 40% of projects will be canceled by 2027 due to reliability concerns”, said Niken Patel, CEO and Co-Founder of Neuron7. “The root cause is hallucinations. In service operations, outcomes are binary. An issue is either resolved or it is not. Probabilistic AI that is right only 70% of the time fails 30% of your customers and that failure rate is unacceptable for mission-critical service”.
That concern shaped how Neuro was built. “We use deterministic guided fixes for known issues. No guessing, no hallucinations — and reserve autonomous AI reasoning for complex scenarios. What sets Neuro apart is knowing which mode to use. While competitors race to make agents more autonomous, we're focused on making service resolution more accurate and trusted”, Patel explained.
At the heart of Neuro is the Smart Resolution Hub, Neuron7’s central intelligence layer that consolidates service data, knowledge bases and troubleshooting workflows into one conversational experience. This means a technician can describe a problem — say, a diagnostic error in an MRI scanner — and Neuro can instantly generate a verified, step-by-step solution. If the problem hasn’t been encountered before, it can autonomously scan through thousands of internal and external data points to identify the most likely fix, all while maintaining traceability and compliance.
Neuro’s architecture also makes it practical for real-world use. It integrates seamlessly with enterprise systems such as Salesforce, Microsoft, ServiceNow and SAP, allowing companies to embed it within their existing support operations. Early users of Neuron7’s platform have reported measurable improvements — faster resolutions, higher customer satisfaction and reduced downtime — thanks to guided intelligence that scales expert-level problem solving across teams.
The timing of Neuro’s debut feels deliberate. As organizations look to move past the hype of generative AI, trust and accountability have become the new benchmarks. AI systems that can explain their reasoning and stay within verifiable boundaries are emerging as the next phase of enterprise adoption.
“The market has figured out how to build autonomous agents”, Patel said. “The unsolved problem is building accurate agents for contexts where errors have consequences. Neuro fills that gap”.
Neuron7 is building a system that knows its limits — one that reasons carefully, acts responsibly and earns trust where it matters most. In a space dominated by speculation, that discipline may well redefine what “intelligent” really means in enterprise AI.