Take charge of your finances with these top budget monitoring apps that make tracking spending simple, smart, and stress-free.
Updated
November 27, 2025 3:26 PM
.webp)
A phone next to a laptop, displaying a stock market app. PHOTO: UNSPLASH
Managing personal finances can feel overwhelming, especially with the countless expenses we juggle daily. Thankfully, budget monitoring apps are hereto save the day. These handy tools help you track your spending, set financial goals, and build better money habits—all from the convenience of your smartphone.
Whether you're saving for a vacation, paying off debt, or just trying to avoid those end-of-the-month surprises, budget tracker apps can provide clarity and control over your finances. Here are 5 budget monitoring apps that will keep your spending on track.
If simplicity is what you’re after, Monefy is the solution. Known for its highly intuitive interface, Monefy lets users track their spending with just a few taps. Unlike many budget apps that overwhelm you with features, Monefy focuses on the essentials, making it great for beginners or anyone looking for a straightforward way to manage their money.
Monefy is perfect for users who want a no-frills app to track spending or beginners just dipping their toes into budgeting.
Budgeting doesn’t have to feel like a chore, and Fortune City proves just that. This app gamifies your financial habits by turning expense tracking into a city-building game. Every category of spending contributes to your virtual city’s development, making it an enjoyable way to visualize where your money is going.
Fortune City is ideal for those who find traditional budgeting boring or intimidating and want a fun way to stay consistent.
Jupiter combines the best of both worlds: digital banking and budgeting. This app integrates directly with your bank account, automatically categorizing transactions and providing insights into your spending patterns. It’s not just a budget tracker—it’s a full-fledged financial assistant.
Jupiter is best for users who want a hands-off budgeting experience and prefer an all-in-one app for banking and money management.
Inspired by the envelope budgeting method, GoodBudget offers a digital twist on this classic approach. Instead of physical envelopes, you allocate your money into virtual "envelopes" for different spending categories. This app encourages disciplined spending and is particularly effective for budgeters who like to plan ahead.
GoodBudget is ideal for planners who like a structured approach to budgeting and don’t mind manual tracking.
Wally is a feature-packed app designed for users who want deep insights into their spending habits. Its sleek design, multi-currency support, and detailed financial reports make it a standout option, especially for frequent travelers or professionals juggling multiple accounts.
Wally is perfect for users who want advanced budgeting tools and detailed insights, especially those with international financial needs.
Budget monitoring apps are powerful tools that simplify the often-daunting task of managing your finances. Whether you’re drawn to the playful gamification of Fortune City, the structured approach of GoodBudget, or the all-in-one convenience of Jupiter, there’s an app tailored to your preferences and goals.
These apps don’t just track your spending—they help you build better habits, gain financial clarity, and take control of your money. With the right app in your pocket, managing your budget becomes less of a chore and more of are warding journey toward financial freedom. So why wait? Choose an app, start tracking, and watch your financial confidence grow!
Keep Reading
The hidden cost of scaling AI: infrastructure, energy, and the push for liquid cooling.
Updated
December 16, 2025 3:43 PM

The inside of a data centre, with rows of server racks. PHOTO: FREEPIK
As artificial intelligence models grow larger and more demanding, the quiet pressure point isn’t the algorithms themselves—it’s the AI infrastructure that has to run them. Training and deploying modern AI models now requires enormous amounts of computing power, which creates a different kind of challenge: heat, energy use and space inside data centers. This is the context in which Supermicro and NVIDIA’s collaboration on AI infrastructure begins to matter.
Supermicro designs and builds large-scale computing systems for data centers. It has now expanded its support for NVIDIA’s Blackwell generation of AI chips with new liquid-cooled server platforms built around the NVIDIA HGX B300. The announcement isn’t just about faster hardware. It reflects a broader effort to rethink how AI data center infrastructure is built as facilities strain under rising power and cooling demands.
At a basic level, the systems are designed to pack more AI chips into less space while using less energy to keep them running. Instead of relying mainly on air cooling—fans, chillers and large amounts of electricity, these liquid-cooled AI servers circulate liquid directly across critical components. That approach removes heat more efficiently, allowing servers to run denser AI workloads without overheating or wasting energy.
Why does that matter outside a data center? Because AI doesn’t scale in isolation. As models become more complex, the cost of running them rises quickly, not just in hardware budgets, but in electricity use, water consumption and physical footprint. Traditional air-cooling methods are increasingly becoming a bottleneck, limiting how far AI systems can grow before energy and infrastructure costs spiral.
This is where the Supermicro–NVIDIA partnership fits in. NVIDIA supplies the computing engines—the Blackwell-based GPUs designed to handle massive AI workloads. Supermicro focuses on how those chips are deployed in the real world: how many GPUs can fit in a rack, how they are cooled, how quickly systems can be assembled and how reliably they can operate at scale in modern data centers. Together, the goal is to make high-density AI computing more practical, not just more powerful.
The new liquid-cooled designs are aimed at hyperscale data centers and so-called AI factories—facilities built specifically to train and run large AI models continuously. By increasing GPU density per rack and removing most of the heat through liquid cooling, these systems aim to ease a growing tension in the AI boom: the need for more computers without an equally dramatic rise in energy waste.
Just as important is speed. Large organizations don’t want to spend months stitching together custom AI infrastructure. Supermicro’s approach packages compute, networking and cooling into pre-validated data center building blocks that can be deployed faster. In a world where AI capabilities are advancing rapidly, time to deployment can matter as much as raw performance.
Stepping back, this development says less about one product launch and more about a shift in priorities across the AI industry. The next phase of AI growth isn’t only about smarter models—it’s about whether the physical infrastructure powering AI can scale responsibly. Efficiency, power use and sustainability are becoming as critical as speed.