Technology

Have we ignored drones amidst this AI wave? The recent war between India and Pakistan proved that the future of warfare lies with drones. India massively lags behind countries like China, Israel, and Turkey in drone technology. Indian private companies, including startups, have so far focused on using imported drones for land surveying, infrastructure monitoring, agriculture, logistics and other consumer use cases. The country has ignored manufacturing drones for the defence industry. Thankfully, the situation is changing. The Government of India (GOI) is launching a Rs 2 billion ($234 M) incentive programme for civil and military drone makers to reduce their reliance on imported components. A recent study estimates that drone manufacturing can become a $23B industry in the next 10 years. While agriculture will have the largest drone use case, defence won't be left behind. GOI recognises that India must manufacture drones to become self-sufficient in defence. Once the investors realise that the government could be a big buyer of military drones, they will start funding drone manufacturing startups. An increasing Indian defence budget, with drones playing a significant role in the overall defence strategy, is a strong tailwind that will propel drone manufacturing in India. However, there is no magic bullet to make India a drone manufacturing powerhouse. It's not a problem that can be solved by throwing billions of dollars. Modern drones are complex machines with advanced engineering components like FCU (Flight Controllers), ESC (Electronic Speed Controllers), IMU (Inertial Measurement Units), Ultrasonic sensors, GPS modules, Motors, Frames, Propellers, Chassis, etc. Manufacturing drones at scale requires tight tolerances, lightweight frames, and high-density PCB designs. Indian SMEs and startups lack the precision engineering expertise to manufacture these components. It will take years, if not decades, before India is ready to manufacture these on a large scale. On top of all the hardware challenges, India suffers from software gaps in real-time edge computing, computer vision, and swarm intelligence. However, I don't expect software to be a bottleneck. The country has enough talent to build stacks for Autonomous Navigation and Simultaneous Localisation and Mapping Technology. I expect the hardware to be a far bigger challenge. The big question is how quickly we can upskill the manufacturing workforce and build labs and factories to overcome precision engineering challenges. This will determine our tryst with drone manufacturing. #India #Drones #Startups #Manufacturing

A $4.4B Supply Chain Revolution Just Got the Green Light 🚁 This could change the game. 🎯 The FAA just dropped their 700-page BVLOS (Beyond Visual Line of Sight) rule proposal—and it's the regulatory breakthrough the logistics industry has been waiting for since 2021. 📋 🔑 Key BVLOS Highlights That Matter: Corporate responsibility model 🏢 - Companies (not individual pilots) manage compliance Dual pathways 🛤️: Permits for low-risk ops, Certificates for large-scale operations Drones up to 1,320 lbs ⚖️ - Way beyond current 55 lb Part 107 limits Automated Data Service Providers 🤖 - FAA-approved UTM systems manage traffic Operations over people allowed 👥 (with restrictions) Air corridors 🛫 for predetermined, scalable routes 🇺🇸 The US Numbers (Finally) Don't Lie: Drone delivery market exploding from $1.08B (2025) → $4.40B (2030) 📈 Drone units scaling 8x: from 32,456 to 275,703 units by 2030 🔢 Last-mile costs slashed by 93% with optimized drone routes 💰 ⚡ The Game-Changing Impact No more individual waivers. No more regulatory roadblocks. This 700-page rule creates a standardized pathway for: Package delivery at scale 📦 Medical supply chains to remote areas 🏥 Agricultural monitoring across vast territories 🌾 Emergency response operations 🚨 Infrastructure inspections 🔍 But here's the reality check: We're playing catch-up. ⏰ 🇨🇳 While the US was stuck in regulatory limbo, China was scaling: Meituan: 450,000+ commercial deliveries across 53 urban routes 🏙️ SF Express: 12,000 daily deliveries, 800-2,000 daily takeoffs in one region alone 📊 JD.com: Operating since 2016, now delivering to the Great Wall of China 🏯 China's goal: 10% of ALL deliveries by drone within 5-10 years 🎯 🚀 The opportunity to catch up is REAL (But the Window is Closing): While Meituan delivers milk tea in dense urban Shenzhen in under 15 minutes ⏱️, US companies like Walmart and Wing are finally proving 19-minute delivery times. The infrastructure gap is real, but not insurmountable. 💪 The strategic question This isn't just about drones—it's about reimagining what "fast delivery" means in 2025 and beyond. The companies moving now will own the advantage when the final rule drops in Q1 2026. ⚡ The race is on. China has a head start. But American innovation + regulatory clarity = game changer. 🏁 What's your take? Is your organization ready for the drone delivery revolution? 💭 #SupplyChain #Innovation #Truckl #FutureOfLogistics #LastMile

Expanding AI Horizons through the Rise of Intelligent Devices One area of excitement is the growing use of drones in Chinese E-commerce. China is making significant strides in the drone sector, showcasing advancements that lead the global market. Recent developments highlight the transformative impact of drones across various industries: • Logistics: In Anyang, a logistics drone completed a 2.2 km flight delivering 8 cups of milk tea, marking the launch of the city’s first point-to-point drone route. This initiative aims to expand drone applications in emergency rescue, urban management, and more. • Efficiency: Nanjing has introduced new drone routes, including a cross-river delivery that takes just 4 minutes, compared to the 70 minutes required by bike. • Rural Logistics: In Songyang, a drone completed a 16 km round-trip delivery, addressing the “last mile” logistics challenge in rural areas. These examples are just the beginning. In the next 2-3 years, we expect even more scenarios and real-life applications at scale. Market Insights • Revenue Projections: China’s drone market is projected to reach US$1.5 billion in 2024, with an annual growth rate of 4.3% CAGR from 2024 to 2028. • Market Volume: By 2028, the market volume in China is anticipated to reach 3.5 million units. • Global Leadership: China is home to DJI, the world’s largest drone manufacturer, holding approximately 75% of the global market share. American Intel holds 4%, followed by Chinese manufacturer Yuneec at 3.6%. The rapid advancements in China’s drone industry underscore the country’s leading position and the vast potential for growth and innovation.

Recently, Hospitality Net asked their Digital Marketing in Hospitality panel how hotels could use AI to shift bookings from OTAs to their direct channels. You might find this answer interesting: In the near term, the biggest opportunities AI provides for driving direct revenue revolve around creating richer, more personalized experiences at each stage of the guest journey. Hotel marketers can use AI to better segment potential guests based on behaviors and deliver content and offers — at scale — that match those segments’ intent. Increasingly, you can let the AI select and orchestrate campaign messages, images, and offers that align with the needs of potential guests, and drive conversion. Similarly, these tools can provide intelligent rate displays and offer attractive upsell opportunities to guests to improve the revenue you achieve during each stay. Real-time guest service during the booking process, including chat, can help improve that experience and increase conversion rate.  Of course, the guest journey doesn’t end at time of booking. Again, savvy hotel commercial teams are beginning to put AI to work to upsell and cross-sell on-property experiences during the pre-arrival and on-property stages of the guest journey to drive greater share of wallet. And, of course, intelligent, automated post-stay campaigns are beginning to produce results in driving repeat bookings from past guests.  In the longer term, we’ve not yet seen how universal access to AI assistants will shape guest behavior. These tools are likely to shift the way guests interact with information and experiences every bit as much as the internet, mobile, and social media have. We should expect to see new marketing and distribution channels that make it easy for us to reach guests directly — and new gatekeepers who seek to insert themselves into that process. Every silver lining comes wrapped in its own cloud.  Regardless, these benefits come with a cost. Hoteliers must take a serious look at their existing tech stack and team skills to ensure they’re ready to put these tools to work. Take a look at the partners you work with. Do they make it easy to connect with new sales and marketing partners? Do they have a well-articulated vision for how they’ll incorporate AI into their products? Have they begun to deliver on that vision? If so, you’re in great shape. If not, it may be time to start looking at alternatives.  And, finally, don’t ignore your people. Does your team have the skills, the resources, and the vision needed to adapt to a changing customer and technology landscape? You will want to give them the support they need to quickly adjust as guest behaviors — and those of your competitors — evolve. The hoteliers who are able to learn the fastest, and put those learnings to use, are the ones most likely to succeed at driving more direct business as AI becomes more common. And there’s nothing artificial about that. #AI #hospitalitymarketing

If you are an organisation using AI or you are an AI developer, the Australian privacy regulator has just published some vital information about AI and your privacy obligations. Here is a summary of the new guides for businesses published today by the Office of the Australian Information Commissioner which articulate how Australian privacy law applies to AI and set out the regulator’s expectations. The first guide is aimed to help businesses comply with their privacy obligations when using commercially available AI products and help them to select an appropriate product. The second provides privacy guidance to developers using personal information to train generative AI models. GUIDE ONE: Guidance on privacy and the use of commercially available AI products Top five takeaways * Privacy obligations will apply to any personal information input into an AI system, as well as the output data generated by AI (where it contains personal information).  * Businesses should update their privacy policies and notifications with clear and transparent information about their use of AI * If AI systems are used to generate or infer personal information, including images, this is a collection of personal information and must comply with APP 3 (which deals with collection of personal info). * If personal information is being input into an AI system, APP 6 requires entities to only use or disclose the information for the primary purpose for which it was collected. * As a matter of best practice, the OAIC recommends that organisations do not enter personal information, and particularly sensitive information, into publicly available generative AI tools. GUIDE 2: Guidance on privacy and developing and training generative AI models Top five takeaways * Developers must take reasonable steps to ensure accuracy in generative AI models. * Just because data is publicly available or otherwise accessible does not mean it can legally be used to train or fine-tune generative AI models or systems.. * Developers must take particular care with sensitive information, which generally requires consent to be collected. * Where developers are seeking to use personal information that they already hold for the purpose of training an AI model, and this was not a primary purpose of collection, they need to carefully consider their privacy obligations. * Where a developer cannot clearly establish that a secondary use for an AI-related purpose was within reasonable expectations and related to a primary purpose, to avoid regulatory risk they should seek consent for that use and/or offer individuals a meaningful and informed ability to opt-out of such a use. https://lnkd.in/gX_FrtS9

In an era where data sharing is essential and concerning, six fundamental techniques are emerging to protect privacy while enabling valuable insights. Fully Homomorphic Encryption involves encrypting data before being shared, allowing analysis without decoding the original information, thus safeguarding sensitive details. Differential Privacy adds noise variables to a dataset, making decoding the initial inputs impossible, maintaining privacy while allowing generalized analysis. Functional Encryption provides selected users a key to view specific parts of the encrypted text, offering relevant insights while withholding other details. Federated Analysis allows parties to share only the insights from their analysis, not the data itself, promoting collaboration without direct exposure. Zero-Knowledge Proofs enable users to prove their knowledge of a value without revealing it, supporting secure verification without unnecessary exposure. Secure Multi-Party Computation distributes data analysis across multiple parties, so no single entity can see the complete set of inputs, ensuring a collaborative yet compartmentalized approach. Together, these techniques pave the way for a more responsible and secure data management and analytics future. #privacy #dataprotection

📊 Your apps are spying on you, but will DPDPA enforcement protect you from it? Probably not. With the DPDP Act introduced in '23, and enforcement being rolled out from November '25 it seems governments are finally making moves to protect consumer data. But what are they really protecting? ❓Sure, there’s effort around protecting the customer personal data: phone number, email, bank statement (keen to see how this enforced by the way, at this point it feels like every loan app out there has my number) But what about your second level data: the behavioral, inferred data, and the profiling story? 🚨 I've written about this in the past - we joke about how apps are listening in to our everyday conversations, but that isn't far from the truth. Apps are silently detecting other apps installed on your phone without consent. And it doesn’t seem like any privacy laws are protecting us from this anytime soon. Here's the thing. I honestly don’t care who has my number anymore. It’s probably been leaked, sold or scraped by now. What I do care about is profiling done without my knowledge. Example: Zomato checks forRedbus, OYO, & fantasy gaming. Swiggy checks for Zara, FirstCry, and others. (Why does a food app need to know that I shop for baby products?). And this isn’t theoretical. This can and does lead to discriminatory pricing: different loan rates, insurance premiums or offers based on assumptions inferred from your app list My problem isn’t just that this happens. It’s that I don’t even know. On iOS, up to 50 such “silent queries” are allowed. On Android? Up to 1000.  And while GDPR has laws against PII data usage & AI profiling, clearly they aren’t enforcing this This also seems to be a limitation of the DPDP Act. It’s built around the themes of user consent, purpose limitation, data minimisation, and data fiduciary accountability. It isn’t built around restricting customer profiling or preventing surveillance. So then, paradoxically: ✅ Asking for explicit customer data (PAN / Aadhar) is clearly regulated ❗Inferring behaviour via app installs or transaction patterns without the customer’s knowledge is not, which is actually even more invasive than explicit PII data! Ideally collecting this data should fall under the data minimization / purpose limitation themes, but that doesn’t seem to be the lens that DPDP has taken at this point. And because the collection of this data is framed as a “fraud / risk” need, and / or as operational metadata it often bypasses the minimization / limitation themes, when it is essentially behavioral fingerprinting, and often more revealing than regulated personal data! Privacy isn’t just about what we give away knowingly. (and since we don’t know we can’t file a complaint). It’s also about what gets extracted without us knowing. We need better answers. And stronger laws 🧠 Deep dive in comments.

"But we’re not a big company!" DPDP fines don’t care. "It’s just a small app update." That’s how it all starts. • You collect a bit more data. • Then a bit more. Before you know it, you’re storing sensitive information without proper protection. Ignoring user consent. Neglecting security. And you tell yourself - this is what innovation looks like, right? Growth. Data-driven decisions. No limits. WRONG. Companies think speed trumps structure - until it doesn’t. The DPDP Act doesn’t bend for innovation excuses. It demands accountability. That "small oversight" isn’t small anymore. Non-compliance can mean fines up to ₹250 crore. Now, Web and App development companies are uniquely impacted by the DPDP Act. Because you often serve as the frontline collectors and processors of personal data. And if you’re building something big for your clients, like a digital lending platform, you need structure. As for the companies, without privacy compliance, your business will crumble. And you’ll have nothing left for the users you’re trying to serve. But the good thing is that this is entirely preventable. So what I suggest here is: 1) Conduct a data audit every quarter. Identify what you collect and eliminate what’s not important. 2) Implement Privacy by Design. Merge data protection into your development process from day one. 3) Educate your team on the DPDP Act. Make sure everyone understands their role in compliance. 4) Stay updated on legal changes. Assign someone to monitor updates to data protection laws. 5) Put user trust first. Be transparent about data practices and give users control. The end goal here is to be intentional. It’s to protect your users. Because once their trust is gone, you don’t get it back. And remember, the DPDP Act isn’t here to slow you down - it’s here to make sure you last. ---  👉 TL;DR: Privacy compliance isn’t optional. Follow DPDP regulations now, or risk losing trust - and paying the price later.

Meet MS Dhoni-backed defence startup, which is emerging as one of India's leading drone technology companies! Founded in 2015 by Agnishwar Jayaprakash, the company gained huge momentum when cricket icon MS Dhoni invested in and became its brand ambassador in 2022. Let’s set the stage with the key facts: 1. Fleet size: Over 400 drones and 500+ pilots (as of 2024). 2. Employees: 3,000+ employees (2024). 3. Market Presence: Operations in India and 26 global markets. 4. Valuation: Reached Rs 21,352.5 Crore in 2023. 5. Annual Revenue: Crossed Rs 120 crore in FY 2023-24. In the seed Round (2018), they raised Rs 2 crore from private investors and in series A (2022), they raised Rs 35 crore led by VC firms, with MS Dhoni's investment firm. In total, MS Dhoni acquired a 5% stake in 2022, serving as both investor and brand ambassador. In Series B (2023), they finally picked up Rs 150 Crore from many investors. In terms of revenue, it maintained 120% year-over-year growth between 2020-2024 and expanded from 15 enterprise clients in 2018 to 300+ by 2024. Started with agricultural drones, now offers 70+ drone-based services across sectors like agriculture, surveillance, delivery, sanitisation, industry purposes and others. With a Rs 15 crore for border surveillance technologies, it has partnered with ISRO & IIT Madras for satellite imagery validation and R&D collaboration. This is none other than Garuda Aerospace Private Limited. Unexplored Raj perspectives: 1. Agriculture: Serviced over 8 million acres of farmland across India, and it has reduced pesticide usage by 30% through precision spraying. It also lowered farming input costs by 20-25% for farmers and increased crop yields by 15-20% through data-driven farming. 2. Infrastructure & Real Estate: Reduced large structures from weeks to hours. Lowered infrastructure monitoring costs by 60%. Eliminated human risk in inspections and improved construction progress tracking accuracy by 40%. 3. Energy: It conducted thermal imaging for 2,000+ MW of solar installations and increased fault detection in solar panels by 35%. Having inspected 50,000+ km of power lines, it's also provided surveillance for 8 major pipeline projects in oil and gas. 4. Healthcare & Emergency: It has transported critical supplies to 500+ remote villages with 20000+ residents. It's also reduced emergency medicine delivery time by 70% in rural areas and has been deployed for 12 natural disaster response operations. 5. Defence & Security: It's enhanced monitoring capabilities across 700+ km of sensitive borders. Participated in 25+ search and rescue operations. Provided aerial support for 40+ major public events. 6. Environmental Impact: Apart from lowering agricultural carbon emissions by 30% through precision farming, it has reduced pesticide and fertiliser runoff into water systems by 25%. Garuda is truly growing India's abilities in the defence industry! Did you know about them? #india #defence #investing #startup

My #WiT2025 takeaways (1/10): Hospitality Show-off Luxury is dead. Long live Meaning. The new battleground in Asia Pacific hospitality is not distribution or price. It's Experience Orchestration. If your tech stack creates friction, you're losing the most valuable guest. 1. The Luxury Pivot: From Having to Becoming Luxury is shifting from material expense ("bling") to profound personal connection and purpose. Top-tier clients are moving from having (material goods) to becoming (experiences), favoring experiences that emphasize social impact or personal immersion. Some panelists therefore mentioned that the core metric for success is moving beyond RevPAR and occupancy to the Return on Emotional Investment (ROE). Loyalty is no longer just driven by points, but in some cases by co-creation and "money-can't-buy experiences", such as COMO Hotels and Resorts collaborating with NASA, as mentioned by Puneet Mahindroo during WiT (Web in Travel). 2. The Crisis of Data Orchestration While distribution channels are largely "solved" (or at least manageable at scale today), the biggest challenge is Experience Orchestration. Systematic data fragmentation still prevents a unified view of the guest, meaning technology operates in silos (pre-stay versus in-stay, F&B, spa, rooms) while the guest interacts with the hotel as a single entity. This causes visible friction: even guests who pre-check-in online frequently waste time at the front desk being asked for information they have already provided. This friction is most acute during the transition from the platform (mostly OTA but also direct) to the physical check-in. This aspect is key as a better in-stay experience may increase the probability for a guest to return by 3.8x according to panelists. 3. OTAs as Experience Partners, Not Gatekeepers In the long standing “love-hate” relationships between OTAs and Hotels, Online Travel Agencies (OTAs) are pushing to redefine their role, shifting from being mere "gatekeepers" to genuine experience partners. For example, according to Xing Xiong, COO of Trip.com, more than 50% of guest queries on platforms like Trip.com occur before the booking is finalized. By providing AI-enabled tools and pre-sale support, OTAs aim to reduce customer friction and increase conversion. 4. Scaling Independent Hospitality Independent hotel groups, such as Worldwide Hotels (WWH), benefit from flexibility and agility. As Carolyn Choo, her CEO, pointed out, the democratization of technology, especially AI, acts as an "equalizer," enabling independent operators to adopt powerful, non-proprietary revenue management and guest experience tools. In highly fragmented sectors, like luxury villas and rentals, scaling is best achieved through an M&A roll-up strategy as mentioned by Stephanie Chai from The Luxe Nomad: acquiring specialized property management companies to gain scale and market expertise. #HospitalityTech #CustomerExperience #LuxuryTravel #AI #TravelStrategy #TheWayForward