Data, Analytics & AI
Digital Engineering
Digital Experience
Cloud & Infrastructure
Digital Marketing
Solutions
Field Sales Platform
Who We Are
Our People
Our Commitments
Our Way of Working Accelerating faster go-to-market.
Blogs Insights and our point of views.
Case Studies
Press Releases
POVs
Industries
Healthcare
Patient experiences engineered for the consumer expectations of 2026.
Insurance and Warranty
Sales, claims, and modernization - Sundew has shipped most defensively.
Luxury and Retail
Digital commerce solutions for the global luxury houses and lifestyle D2C brands.
Education
Modernizing and building applications, platforms, and digital presence.
Real Estate
Customer-facing applications and brand digital presence with marketing funnels.
Travel and Hospitality
Booking, stay, and post-trip unified into one intelligent guest journey.
Energy & Utility
Manufacturing
Food & Beverage
Government
Professional Services
Media & Entertainment
Blogs Latest Insights
Case Studies Success Stories
Press Releases Company Updates
POVs Company Updates
Have something on your mind? Let's create something amazing together.
* marked fields are mandatory
In the dynamic landscape of EnergyTech, the synergy between Artificial Intelligence (AI) and Data Science has emerged as a game-changer. Artificial Intelligence (AI) is fundamentally transforming the energy sector landscape, reinventing power generation, distribution, and consumption dynamics.
The intricate and technology-driven realm of Energy & Utilities constantly urges entrepreneurs to harness innovations swiftly and comprehensively. Recognizing the potential of artificial intelligence to elevate human productivity, a staggering 92% of Energy & Utilities companies have already invested in AI or are poised to do so within the next two years, aiming to gain a competitive edge.
Incorporating AI and data science in various aspects, from smart grid management to renewable energy forecasting and even enhancing the safety of nuclear power plants, has created a paradigm shift that is steering the energy industry toward a future characterized by heightened efficiency, sustainability, and security.
With artificial intelligence emerging as a pivotal technology shaping the future of energy & utilities, let's delve into the transformative power of these technologies, highlighting the top 5 applications of AI and data science in EnergyTech that promise the most significant returns.
Smart grids are advanced electricity supply networks that leverage digital communications technology to respond dynamically to local changes in usage. AI has ushered in a new era for Smart Grid Management. By harnessing predictive analysis, AI ensures the reliability of grid infrastructure. Data Science further optimizes grid performance and accurately forecasts load patterns, leading to more efficient energy distribution.
AI plays a pivotal role in the management of smart grids, advanced electricity supply networks leveraging digital communications technology to dynamically respond to local changes in usage. Through the deployment of AI algorithms, predictive capabilities emerge as a valuable asset. By analyzing historical and real-time data, AI predicts consumption patterns, empowering utilities to allocate resources with greater efficiency.
Furthermore, AI contributes to optimizing resource allocation in smart grids. During sudden spikes in demand, AI steps in to enhance electricity distribution, strategically directing power where it's most needed. This not only ensures a more balanced distribution but also mitigates the risk of blackouts during peak usage periods.
2. Predictive Analytics for Equipment Maintenance
Integrating AI and Data Science in EnergyTech is pivotal in predicting equipment failures. Through the strategic integration of AI, energy companies gain the ability to anticipate and predict when their equipment is prone to failure or in need of maintenance. Machine learning analyzes data from diverse sources, including usage statistics, weather data, and historical maintenance records to predict potential failures in systems and subsystems before they transpire. This predictive approach minimizes downtime, curtails repair costs, and elevates the overall reliability of energy infrastructure.
Simultaneously, Data Science enables real-time monitoring that can be linked to an app to facilitate proactive maintenance from both the consumer and the provider’s ends, enhancing overall equipment efficiency and preventing costly breakdowns. Energy AI-driven predictive maintenance emerges as a proactive solution, fostering operational efficiency and fortifying the resilience of energy systems.
3. Demand Response Management
Effective demand response management (DRM) is a critical strategy within the energy sector, designed to optimize electricity consumption and maintain the stability of the electrical grid. AI in energy management introduces a transformative dimension to DRM by establishing an interactive link between energy providers and consumers, facilitating real-time responses to shifts in energy demand. This strategic approach involves the dynamic adjustment of electricity usage, primarily within commercial and industrial entities, in response to signals from grid operators or energy providers.
The overarching goal is to balance supply and demand, particularly during peak periods, by initiating load shedding to alleviate strain on the grid and avoiding the necessity for costly infrastructure upgrades.
4. Energy Trading
The predictive capability of AI serves as a sophisticated analyst of intricate market dynamics within the energy trading sector. Operating with remarkable speed and precision, it processes real-time data encompassing pricing, demand, and supply trends. This empowers energy companies to make well-informed and profitable trading decisions. Beyond its analytical abilities, Data Science applications and AI in energy trading and market analysis optimize strategies, ensuring effective participation in energy markets, and executing numerous trades in milliseconds. This high-speed functionality optimizes energy portfolios, simulates market scenarios, analyzes sentiment, automates tasks, and dynamically adapts to changing market conditions, enabling the detection of market opportunities and risks that may elude human traders.
Through analytics, demand fluctuations are anticipated and managed, contributing to enhanced AI-driven energy efficiency, cost reduction, and a smoother transition toward renewable energy sources. Machine learning in the energy sector excels in demand forecasting by monitoring individual customers' daily consumption patterns. This optimization allows for more efficient resource usage, leading to cost reductions in energy production.
5. Renewable Energy Integration and Storage
AI and data science in EnergyTech revolutionizes the storage and distribution of energy derived from renewable sources. By factoring in dynamic variables such as demand, supply, pricing, and grid conditions, AI algorithms precisely determine the optimal moments to store energy, when to release it, and the optimal distribution quantities. Particularly for renewable sources such as wind and solar, AI algorithms, backed by Data Science, meticulously analyze a blend of weather forecasts, historical generation data, and real-time conditions.
This comprehensive approach equips energy providers with the ability to accurately predict the availability of renewable energy, facilitating enhanced balancing of supply and demand dynamics. Further benefits of AI in the Energy sector include smart energy storage that strategically captures excess energy generated during peak periods, storing it for use during times when these sources are not actively producing electricity. Beyond general applications, energy storage takes on critical importance in vital facilities such as hospitals, data centers, and emergency services. Overall, the application of artificial intelligence in renewable energy systems proves advantageous in reducing dependence on weather conditions.
The Future of AI and Data Science in the Energy Industry
The future of AI in the energy sector is promising, poised to optimize energy generation, distribution, and consumption continually. With the evolution of increasingly sophisticated data-driven solutions, businesses can expect enhanced efficiency of renewable energy sources, fortifying grid stability and mitigating greenhouse gas emissions. The prevalence of smart grids and demand response management will empower consumers to control their energy consumption proactively.
Predictive maintenance will emerge as a pivotal force facilitated by AI and data science in EnergyTech, minimizing downtime and elevating equipment reliability. AI's contributions to carbon capture and storage efforts will actively contribute to the global fight against climate change. As technology progresses and AI becomes more ingrained in energy systems, businesses can look forward to a more sustainable and efficient energy landscape.
Related Blogs
Blog
How Companies Use AI-enabled Digital Transformation in Travel
Imagine being stuck in heavy traffic with your flight boarding in an hour. In the past, you’d just panic and pray. Today, your AI tracks your GPS location and instantly purchases a priority security pass for you, saving you 20 minutes at the airport. If the traffic is really bad, the AI moves you to the next flight before you even enter the terminal. This level of digital transformation in travel to improve customer experience is a total game-changer. This shift is already the new standard: according to Statista, roughly 7 in 10 travelers across North America now rely on AI for real-time personalization. By late 2026, AI-enabled digital transformation in travel will become even more seamless, neutralizing chaos before it causes passenger stress.How Companies Use AI-Enabled Digital Transformation In TravelRight now in 2026, digital transformation in travel stands as far more than "just for show." Industry leaders like Expedia, Air France, Marriott, Booking.com, and Delta Air Lines have moved past the "what-if" stage. They currently use AI-enabled digital transformation in their core operations to maximize customer experience.Expedia Integrates A ChatGPT-Powered Trip PlannerExpedia uses this conversational AI to help travelers find the perfect vacation through simple, natural dialogue. By letting AI handle common inquiries and planning tasks, they have successfully reduced customer support calls.Marriott Uses "M-Live" To Track Traveler SentimentMarriott utilizes this real-time monitoring system to track traveler sentiment and social media trends as they happen. This data allows them to create highly personalized experiences that have increased direct-to-consumer bookings.Booking.com Uses A Natural Language AI AssistantBooking.com offers an AI assistant that chats with users to build fully customized travel itineraries. This interactive experience keeps travelers engaged on the platform longer, significantly enhancing user retention.Air France Leverages AI-Driven Baggage TrackingAir France uses high-precision AI systems to monitor and sort luggage throughout the entire journey. This smart technology has improved operational reliability and led to a notable decline in lost luggage reports.Delta Air Lines Utilizes Predictive Maintenance and ModelingDelta Air Lines uses advanced AI to identify potential technical issues or weather disruptions before they cause delays. This proactive approach ensures smoother operations and has minimized flight cancellations and downtime.These success stories from industry leaders are not just random wins; they are part of a much larger shift in how travel works today. By examining these examples, we can see how the industry is moving toward core AI strategies that are shaping the future of global travel. 6 AI-Powered Strategies Shaping The Future Of Travel1. Hyper-PersonalizationIn the past, travel companies would just put you into groups like "Business Traveler" and book easily available premium rooms. Today, they use "Agentic AI" to anticipate your tiring day and secure a premium room at a quiet corner far from the elevator. This deep level of personalization isn't just a buzzword but a major revenue driver (Statista) that turns a cold booking into a personal connection. How does it impact: True loyalty grows when you're treated as a person, not a random booking number. When an app understands you this well, it solves problems before you even notice them.2. Predictive InterventionsToday’s travel apps have evolved into predictive intelligence systems. By syncing real-time weather and airport data, these AI-enabled apps spot delays early and act instantly - whether that’s prompting you to leave 15-minutes earlier or snagging a priority pass to bypass security crowds. How does it impact: By acting as a predictive early warning signal, the AI solves travel issues before they even start, to help you move through every checkpoint smoothly and on time. 3. Biometric "Zero-Friction" JourneysYour face and voice have become your passport and boarding pass. AI-powered sensors recognize you instantly, allowing you to walk from the airport curb to your seat on the plane without reaching for a phone or ID. This "invisible" tech handles check-ins in the background, making the journey hassle-free. How does it impact: By removing physical hurdles and long queues, AI-powered travel apps significantly improve passenger satisfaction, allowing you to relax and actually enjoy the premium services at the airport.4. Agent-To-Agent BookingRecent GitHub stats show a sharp rise in “Agentic Workflows,” proving that agent-to-agent working models aren’t just a theory; it's what hundreds of developers are actively coding into reality this year. This evolution is a core part of digital transformation in travel, where your personal AI "agent" now talks directly to an airline's AI to negotiate the best deal on your behalf. How does it impact: It saves you hours of research and guarantees you get the best price every time. Automating the booking process frees you to explore your hotel’s amenities and perks well before you even arrive. 5. Immersion-First Planning (AR/VR)Nowadays, the "search" bar is often replaced by "try-before-you-buy" experiences. Using Augmented Reality (AR), you can walk through a 3D version of a hotel room or a hiking trail before spending a cent. AI analyzes how you respond to these virtual tours to refine its suggestions until the final booking is guaranteed to succeed.How does it impact: By providing a virtual tour, immersion-first tech removes the fear of the unknown and gives travelers the confidence to choose destinations that match their exact taste. 6. Real-Time Language & Cultural "Bridge.Language barriers are pretty much gone nowadays, thanks to AI, marking a pivotal milestone in digital transformation in travel. AI now provides real-time translation through your earbuds, acting as a cultural guide, whispering tips about local etiquette or tipping customs in your ear as you enter a restaurant. How does it impact: AI transforms you from a generic tourist into a welcomed guest. By bridging cultural gaps and helping you connect respectfully with locals, the system ensures you feel at home the moment you arrive.While these strategies set the vision for the future, the real "magic" comes from the app's specific features. Whether you are building for a B2C traveler or a B2B partner, different AI features adapt to solve different problems. B2B vs. B2C Travel Tech: Choosing The Right FeaturesBuilding the right features is essential for any app to function, but their purpose varies depending on who uses them. A B2C app focuses on making travel joyful, while B2B tools are built for speed and business precision.How Do B2B and B2C Companies Use AI In Travel?While the core technology is similar, the AI adapts its approach based on its user. With a traveler on vacation (B2C), AI emphasizes personal touches. With a logistics manager (B2B), AI focuses on efficiency, data analysis, and operational clarity. We see this play out in two different ways:For the Traveler (B2C): It’s the "Heart." Instead of a cold search bar, you get a thoughtful assistant that actually "understands" you. It handles the stressful planning (Statista) and suggests things you’ll love - like a hidden café - because it remembers you prefer a quiet espresso over a loud tourist trap.For the Business (B2B): It’s the "Brain." This side is all about operational speed and precision. It skips the small talk to handle the heavy lifting, such as building an AI-enabled system at an airport to turn fragmented updates from airlines, security, and ground into a unified command center. (BCG)If you want to build a travel app that actually succeeds in the future, you need a clear plan. Here is a simple guide on the best ways to use AI so your users stay happy and loyal. Best Practices For Building AI In A Travel AppBuilding an AI-powered travel app in 2026 is all about making the tech so smooth that it does all the hard work in the background while the traveler just enjoys the trip.Here’s the secret sauce for getting it right:Personalize in real-time: Use AI that adapts your itinerary on the fly based on your current mood, energy levels, and local weather.Keep it real: Program your AI to suggest cool, local, and sustainable spots - not just the big tourist places paying the highest commission. Don't fear the dead zones: Run offline-first AI models on the phone so translation and maps work perfectly even with zero signal or Internet. Play well with others: Build your AI so it can easily "hand off" tasks to other apps, whether it's for digital payments or local health alerts. Automate the boring stuff: Deploy AI that handles repetitive tasks like filling out visa forms or tracking loyalty points without you lifting a finger.Stick to these rules, and you aren't just building another AI model - you’re building a travel companion that nobody wants to leave home without.The Bottom LineThe true winners won't be the ones with the flashiest travel apps, but the ones who use AI to make the "logistics" of travel vanish. We’re talking about flights rebooked before you even feel the panic, and experiences that feel personal before you’ve even arrived.The soul of digital transformation in travel is about taking the "work" out of the trip so you can enjoy your journey. The best technology is the kind you don’t even notice - it simply makes the world feel smaller, friendlier, and much easier to explore.
Hybrid App Vs. Native App – Which one is better?
Technology is progressing rapidly and it is changing the way we live and work. Our huge dependence on smartphones is the best bait for businesses to target the new millennial. For almost everything you can find an app, right from ordering food, playing video games, listening to music to even finding a date for some event, an app can meet every human desire. However, the likings and expectations of users from around the world create certain requirements for apps. They prefer the apps to be fast, user-friendly, highly responsive and reliable.There are multiple factors that determine how to select the best technology for a mobile app. Each technique of developing an app has its own set of perks and shortcomings. This article will outline the major differences between the two similar but at the same time very different mobile app development method — Native and Hybrid Application Development.Here are key differences between native and hybrid mobile appsBoth these methods - native and hybrid have ways to meet diverse needs and purpose of users and developers, but none of them can be said to be the perfect solution. These apps have their pros and cons — both for an app developer and the end user.Pros of Native Apps• Full Integration of DeviceNative Apps come with many functionalities offered by the mobile devices such as cameras, GPS, calendar,s and microphone. These apps help the users to build an experience that is fully enjoyable and provides great exposure.• Works without an internet connectionOne of the striking features of the Native app is that these apps also work without an Internet connection. • Excellent PerformanceIf you are looking to build a high-speed app, then a native app should be your pick. It is designed specifically for some operating systems and provides great performance.• More secure and safeAll the native apps are accessible through the app stores and reviewed by the app store approval team. This provides a certificate of reliability and assurance.Cons of Native Apps• Higher development and maintenance expensesNative apps are quite intricate since they have a different codebase for each platform and to maintain them, it requires a lot of time and effort as developers have to work and support each version natively.• No guarantee that apps will get acceptedOnce the applications are made, they are required to get approval from the Play Store. And it is a lengthy and tedious process because all the applications have to get approved from the store to get featured. Also, there are chances that the application might get rejected and will not be added to the App Store databases. Pros of Hybrid Apps• Unified DevelopmentThe main advantage of Hybrid Apps is that it allows the companies to save a lot of time and money in developing more than a single app for leading platforms.• Works on a single codebaseHybrid Apps are easier to maintain as the developer needs to manage only one codebase. This ensures smooth and efficient productivity.• Fastest development speedHybrid Apps can be built in a very short period of time. These apps require less maintenance as compared to the native apps and are flexible in terms of launching it on another platform.• Efficient ScalingHybrid apps are also known as cross-platform applications which are easy to scale on different platforms and different operating devices. It permits the development team to reuse the code without making much change in the application.Cons of Hybrid Apps• Slow PerformanceHybrid apps are a bit slower because they are based on web technologies and at the same time they are utilizing mobile platforms which can result in poor performance. If the user doesn’t get an impressive experience, then the likelihood of the application becoming popular goes down.• Poor UXA hybrid app doesn’t offer a user that smooth experience like a native app. Also, the users very rarely give a second chance to an application that has a poor user interface.To be precise, it is important to understand the differences between native and hybrid apps. Each has its own strengths and flaws, and the ultimate decision depends almost entirely on your business needs.
Five ways how Chatbots can offer better Customer Service
Chatbots are used everywhere nowadays be it in receiving orders or responding to queries. Most companies are leveraging chatbots for operation purposes to get better outcomes. Many big giants in the industry are referring to chatbots as the next big thing for data management and customer servicing.We are all aware of the buzz that chatbots have created in the business sphere. However, it is a computer program that is capable of initiating a real conversation via chat interface and has a wide range of applications for any type of business. Chatbots are equipped with AI, Machine Learning (ML) and Natural Language Processing have the knack to understand and process human language making it easier to solve human queries.Here’s how chatbots can enhance your customer’s experience:Instant customer service and supportWe are often put on hold while in the middle of a conversation with a customer service representative and this process requires patience and most importantly your customer’s valuable time. Luckily, a chatbot will help you solve this problem. Your customers will never have to wait as a chatbot will answer all your queries in a fraction of second. This allows customer service representatives to focus on more critical issues and leave a positive impact on the customer.Personal service and increased salesChatbot assists in making purchasing decisions, making recommendations based on customers’ preferences and searching for a product catalogue which proves helpful for the customer as well as increases profits for your business. For some reason, if a customer exits a site without making a purchase, the chatbot remembers the last conversation with the customer and makes recommendations accordingly.Access to a larger audienceChatbots allows businesses to access a wide range of audience as there are more than one billion active users who are using messengers or similar applications. It simply means that with just a single click, one can approach more than a billion users.Round the clock availabilityThe purpose of having a chatbot is that customers can initiate a conversation at any time as long as they are using a messenger application on which the chatbot is employed. This proves to be favourable as it can solve any basic issue by a customer during non-working hours.Chatbots can predictChatbot always recollects previously held conversations with a particular customer which benefits the company in predicting the targeted customer base while devising a strategy. The more you know your customer, the better your business will perform.Having a chatbot for your business makes it possible for you to understand your customer requirement which helps in initiating a series of questions. This also allows a business to know the preferences, likes and dislikes, etc. based on these data, an organization can plan the marketing strategy and approach to the target audience.
Thank You!
Excellent!
Successfully subscribed to Sundew Solutions newsletter!
Oops!
Sorry
Something went wrong!