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AI to control solar panels, and enable power sharing? How US Energy Sector startups are leading the AI race

As the global energy landscape evolves to meet the necessities of climate change and burgeoning demand, Artificial Intelligence (AI) and Machine Learning (ML) are rapidly emerging as linchpins for sustainable energy solutions. The nexus between these advanced technologies and energy sustainability is not merely theoretical but manifests in real-world applications, driving tangible benefits. The global AI market in the energy sector is predicted to reach a staggering $19.2 billion by 2028, and the potential of AI to unlock $1.6 trillion in savings by 2030, underpins the seismic shift underway. This transition is not just an indicator of optimized energy management and reduced greenhouse gas emissions but also a fertile ground for startups to innovate and contribute to a more sustainable, efficient, and resilient energy ecosystem.

The Energy Sector in the USA is Booming At a Rapid Pace

The energy sector stands at the cusp of a transformative phase, with AI and ML being the vanguards of this transformation. 

The global AI market in the energy sector is set to ascend at a CAGR of 25.1%, reaching a valuation of $19.2 billion by 2028, a testament to the growing affinity towards AI-driven solutions. The prowess of AI extends to a potential saving of $1.6 trillion for the global energy sector by 2030, embodying the financial prudence of embracing AI.

In terms of efficiency and sustainability:

What AI Can Do for the Energy Sector in the USA?

A few years back, no one knew how AI could be used in the US energy sector. Now, however, we have pretty splendid examples of companies using AI to enhance the customer experience and sustainability further. Let’s go through a few examples.

Customer Experience

AI is still in its infancy and there’s a lot to come. However, thanks to tech partners like Mantra Labs, energy companies in the US are able to leverage modern technology to enhance their customer experience exponentially. GreenBrilliance (a leading solar panel installer in the US) is one such example. The solution developed by GreenBrilliance helps customers know how many solar panels will be required to power a house, how much power does a solar panel produce, and more. Further, it would help them monitor, control, and troubleshoot their solar panels on their smartphones.

Customer experience is one such thing that has started getting attention in the last few years. B2C companies, irrespective of their industry, not only build products or render services but try to provide the best customer experience possible. Reports predict that Solar could fulfill 40-50% of U.S. electricity demand by 2050. Also, the cost of installing and servicing solar panels has also been reduced by 60% over the last decade. This has been possible only through implementing automation, simplifying operations, and bringing transparency to the customer, along with many other things. 

Efficiency and Sustainability

Efficiency and sustainability are the USPs of solar power and AI is helping to boost that further. 

For example, accurate demand forecasting is pivotal for energy efficiency and cost-effectiveness. Startups like GridX are leveraging AI to predict energy demand and optimize power flows, thereby reducing energy costs and enhancing system efficiency.

Companies like Power Ledger are using AI systems to modernize and decentralize grid systems, enabling efficient trade of solar power among neighbors. This fosters a balanced supply and demand, optimized power flows, and improved grid reliability. Moreover, AI-driven innovative energy storage solutions are instrumental in integrating renewable energy into the grid and enhancing energy security.

These diverse applications underscore the boundless potential of AI and ML to revolutionize the energy sector, making it more sustainable, efficient, and resilient.

What Future AI Promises to the US’s Energy Sector?

As AI technology continues to evolve, the horizon of possibilities in the energy sector broadens. Large corporations like Google, Amazon, and Microsoft, alongside agile startups, are exploring the AI energy landscape continuously, indicating a robust and growing ecosystem.

And it’s not only the private sector that is putting effort into harnessing the power of AI. The US Department of Energy (DOE), the National Renewable Energy Laboratory (NREL), and other governmental bodies are also leveraging AI to pioneer new generations of nuclear reactors, develop new solar and wind technologies, and create smart grid systems.

Integration of AI and ML with the energy sector is a narrative of innovation, sustainability, and vast potential. The journey of companies like Green Brilliance Predictum, Heliogen, GridX, Amperio, and Power Ledger illustrates the transformative power of AI and ML in forging a sustainable energy future. As the global AI market in the energy sector burges, the call for startups to innovate and contribute to this burgeoning ecosystem is loud and clear. The narrative of AI and ML in the energy sector is still being written, and startups have a golden opportunity to be the authors of many success stories in this narrative.

Further Readings: Bringing Solar Renewable Energy Closer to Consumers in the USA

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Why Netflix Broke Itself: Was It Success Rewritten Through Platform Engineering?

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Let’s take a trip back in time—2008. Netflix was nothing like the media juggernaut it is today. Back then, they were a DVD-rental-by-mail service trying to go digital. But here’s the kicker: they hit a major pitfall. The internet was booming, and people were binge-watching shows like never before, but Netflix’s infrastructure couldn’t handle the load. Their single, massive system—what techies call a “monolith”—was creaking under pressure. Slow load times and buffering wheels plagued the experience, a nightmare for any platform or app development company trying to scale

That’s when Netflix decided to do something wild—they broke their monolith into smaller pieces. It was microservices, the tech equivalent of turning one giant pizza into bite-sized slices. Instead of one colossal system doing everything from streaming to recommendations, each piece of Netflix’s architecture became a specialist—one service handled streaming, another handled recommendations, another managed user data, and so on.

But microservices alone weren’t enough. What if one slice of pizza burns? Would the rest of the meal be ruined? Netflix wasn’t about to let a burnt crust take down the whole operation. That’s when they introduced the Circuit Breaker Pattern—just like a home electrical circuit that prevents a total blackout when one fuse blows. Their famous Hystrix tool allowed services to fail without taking down the entire platform. 

Fast-forward to today: Netflix isn’t just serving you movie marathons, it’s a digital powerhouse, an icon in platform engineering; it’s deploying new code thousands of times per day without breaking a sweat. They handle 208 million subscribers streaming over 1 billion hours of content every week. Trends in Platform engineering transformed Netflix into an application dev platform with self-service capabilities, supporting app developers and fostering a culture of continuous deployment.

Did Netflix bring order to chaos?

Netflix didn’t just solve its own problem. They blazed the trail for a movement: platform engineering. Now, every company wants a piece of that action. What Netflix did was essentially build an internal platform that developers could innovate without dealing with infrastructure headaches, a dream scenario for any application developer or app development company seeking seamless workflows.

And it’s not just for the big players like Netflix anymore. Across industries, companies are using platform engineering to create Internal Developer Platforms (IDPs)—one-stop shops for mobile application developers to create, test, and deploy apps without waiting on traditional IT. According to Gartner, 80% of organizations will adopt platform engineering by 2025 because it makes everything faster and more efficient, a game-changer for any mobile app developer or development software firm.

All anybody has to do is to make sure the tools are actually connected and working together. To make the most of it. That’s where modern trends like self-service platforms and composable architectures come in. You build, you scale, you innovate.achieving what mobile app dev and web-based development needs And all without breaking a sweat.

Source: getport.io

Is Mantra Labs Redefining Platform Engineering?

We didn’t just learn from Netflix’s playbook; we’re writing our own chapters in platform engineering. One example of this? Our work with one of India’s leading private-sector general insurance companies.

Their existing DevOps system was like Netflix’s old monolith: complex, clunky, and slowing them down. Multiple teams, diverse workflows, and a lack of standardization were crippling their ability to innovate. Worse yet, they were stuck in a ticket-driven approach, which led to reactive fixes rather than proactive growth. Observability gaps meant they were often solving the wrong problems, without any real insight into what was happening under the hood.

That’s where Mantra Labs stepped in. Mantra Labs brought in the pillars of platform engineering:

Standardization: We unified their workflows, creating a single source of truth for teams across the board.

Customization:  Our tailored platform engineering approach addressed the unique demands of their various application development teams.

Traceability: With better observability tools, they could now track their workflows, giving them real-time insights into system health and potential bottlenecks—an essential feature for web and app development and agile software development.

We didn’t just slap a band-aid on the problem; we overhauled their entire infrastructure. By centralizing infrastructure management and removing the ticket-driven chaos, we gave them a self-service platform—where teams could deploy new code without waiting in line. The results? Faster workflows, better adoption of tools, and an infrastructure ready for future growth.

But we didn’t stop there. We solved the critical observability gaps—providing real-time data that helped the insurance giant avoid potential pitfalls before they happened. With our approach, they no longer had to “hope” that things would go right. They could see it happening in real-time which is a major advantage in cross-platform mobile application development and cloud-based web hosting.

The Future of Platform Engineering: What’s Next?

As we look forward, platform engineering will continue to drive innovation, enabling companies to build scalable, resilient systems that adapt to future challenges—whether it’s AI-driven automation or self-healing platforms.

If you’re ready to make the leap into platform engineering, Mantra Labs is here to guide you. Whether you’re aiming for smoother workflows, enhanced observability, or scalable infrastructure, we’ve got the tools and expertise to get you there.

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