Staff augmentation in fintech
Staff augmentation in fintech: staying agile amid market and compliance challenges Building and scaling fintech products is about trust, compliance, and agility. With global markets
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Staff augmentation in fintech: staying agile amid market and compliance challenges Building and scaling fintech products is about trust, compliance, and agility. With global markets
See how AI in staff augmentation makes hiring faster and smarter. Learn how AI recruitment, predictive hiring, AI-powered developer matching, and automated talent sourcing are helping companies build better teams in 2025.
Enterprises are investing in custom silicon for AI to boost performance, cut costs, and improve energy efficiency beyond GPUs.
Traditional software thinking is holding businesses back in the era of AI-first development. Discover why rules-based approaches fail, how data replaces code, and why a mindset shift is important for successful AI projects.
Discover why nearshoring in Central Europe is becoming the go-to strategy for Western scaleups. Learn how IT talent in Hungary, cost-effective staff augmentation, and remote developer teams across Eastern Europe help companies scale efficiently without compromising quality.
Unlock the power of staff augmentation for startups to overcome startup growth challenges. Learn about scaleup IT staffing, startup team extension, and agile developer hiring for flexible growth in 2025 and beyond.
Staff augmentation in fintech: staying agile amid market and compliance challenges Building and scaling fintech products is about trust, compliance, and agility. With global markets
Enterprises are investing in custom silicon for AI to boost performance, cut costs, and improve energy efficiency beyond GPUs.
Traditional software thinking is holding businesses back in the era of AI-first development. Discover why rules-based approaches fail, how data replaces code, and why a mindset shift is important for successful AI projects.
Artificial intelligence is shaping every industry, from healthcare to finance to education. But while AI adoption is accelerating, talent supply hasn’t kept pace. Companies eager to implement AI face a shortage of skilled professionals who can build, manage, and scale AI systems.
The world is generating approximately 402.74 million terabytes of data every single day and that’s more than all the books in every library on Earth combined, created in just 24 hours. What makes this even more fascinating is that much of this data is produced in real time, through social media posts, online transactions, IoT devices, and digital interactions. Today, real-time data is no longer optional but it’s essential for building effective digital systems.
It may surprise many that over 70% of digital transformation projects worldwide fail to deliver expected results. Businesses often invest heavily in automation tools, yet they fall short of creating measurable value. Why does this happen? The reason is clear that automation alone is not enough.
When we think of “automation,” we often picture repetitive tasks handled faster. But in today’s competitive market, speed alone doesn’t guarantee success. What organizations truly need is an AI First approach, a mindset where artificial intelligence isn’t an afterthought but the foundation for driving business value.
See how AI in staff augmentation makes hiring faster and smarter. Learn how AI recruitment, predictive hiring, AI-powered developer matching, and automated talent sourcing are helping companies build better teams in 2025.
Discover why nearshoring in Central Europe is becoming the go-to strategy for Western scaleups. Learn how IT talent in Hungary, cost-effective staff augmentation, and remote developer teams across Eastern Europe help companies scale efficiently without compromising quality.
Unlock the power of staff augmentation for startups to overcome startup growth challenges. Learn about scaleup IT staffing, startup team extension, and agile developer hiring for flexible growth in 2025 and beyond.
According to a recent study, 91% of employees with mentors report higher job satisfaction. This powerful statistic highlights the deep impact mentorship can have, not just on individual career growth, but also on employee engagement, retention, and overall organizational success.
However, as companies scale and diversify, offering personalized one-on-one mentorship to every team member becomes increasingly complex. So the question arises: how can we bring the transformative power of mentorship to thousands or even millions without losing its human touch?
By 2025, the mobile learning market is expected to reach around $94.93 billion and is projected to grow to $287.17 billion by 2030, with an annual growth rate of 24.78%. With smartphones becoming more widely accessible, mobile learning (m-learning) has become an essential part of modern education.
This rapid growth reflects a shift in how people access education, making learning more flexible, interactive, and personalized. Whether it’s students looking for supplementary resources, professionals upskilling on the go, or educators seeking innovative teaching tools, mobile learning apps have revolutionized the way knowledge is shared and consumed. As technology continues to evolve, the demand for well-designed and engaging educational apps is higher than ever, shaping the future of learning across all age groups.
Gone are the days when bankers had to deal with a huge pile of paperwork, and customers at banks had to wait in long queues to get a transaction done.
All thanks to technology, which has the potential to transform banking at an exponentially faster pace.
The world is generating approximately 402.74 million terabytes of data every single day and that’s more than all the books in every library on Earth combined, created in just 24 hours. What makes this even more fascinating is that much of this data is produced in real time, through social media posts, online transactions, IoT devices, and digital interactions. Today, real-time data is no longer optional but it’s essential for building effective digital systems.
As the education technology sector continues to expand rapidly, there is a growing need to develop secure EdTech solutions that not only enhance learning experiences but also protect sensitive data. With the increasing adoption of digital tools in education, from virtual classrooms and learning management systems to AI-driven personalized learning platforms, ensuring security and privacy has become a top priority.
About 91.5% of Google traffic stays on the first page, and only 4.8% of users click through to the second page. This tells us that search isn’t just about keywords anymore, it’s about understanding intent.
Search engines have come a long way, moving beyond simple keyword matching to focus on understanding the intent behind each query. Artificial Intelligence (AI) plays a big role in this by enabling search engines to interpret user behavior and make search results more relevant and personalized. But how does AI actually make this possible? Let’s explore it in this article.
Gone are the days when bankers had to deal with a huge pile of paperwork, and customers at banks had to wait in long queues to get a transaction done.
All thanks to technology, which has the potential to transform banking at an exponentially faster pace.
About 93% of online experiences start with a search engine. AI-powered search enhances user engagement by utilizing machine learning and natural language processing to provide more accurate, context-aware, and personalized results.
Let’s explore how AI-driven search is reshaping personalization and user engagement, and why businesses that ignore it risk falling behind.
Have you noticed how online searches have become more conversational? Whether it’s through voice assistants or typing out detailed queries like “What’s the best pizza near me?” or “How do I fix a leaky tap?” The way people search is changing rapidly. This growing trend toward natural language queries highlights the need for businesses to rethink how they handle search functionality and adapt to this new era of AI-powered search.
Did you know that software bugs cost the global economy around $2 trillion annually in the US in 2020? The consequences of defective software range from lost revenue to security breaches and system failures. As businesses scale and products grow more complex, ensuring software quality at every stage becomes a mission-critical task. This is where automated testing toolkits play an important role in maintaining reliability and efficiency.
In a world where technology is evolving rapidly, relying solely on manual testing is no longer practical for enterprises that need speed, accuracy, and reliability. Automated testing helps organizations deliver high-quality software while making better use of their resources. Let’s dive into how these toolkits improve quality and efficiency at different stages of software development.
In modern software development, Continuous Integration and Continuous Deployment (CI/CD) have become essential for delivering high-quality applications at speed. By automating the development pipeline, CI/CD solutions reduce manual effort, minimize errors, and enhance software reliability. These solutions help organizations scale efficiently while ensuring robust software releases. This article explores the significance of CI/CD, its key components, popular tools, best practices for implementation, and technical considerations for DevOps engineers and agencies, including advanced topics such as Infrastructure as Code (IaC), security integration, microservices deployment, and multi-cloud strategies.
The digital world moves faster every day. Businesses need software that works well to stay ahead. If there’s a bug or a delay, users quickly get frustrated and look for other options. AI-powered Quality Assurance (QA) helps solve these problems. It speeds up testing and makes it more accurate. It finds bugs early, which helps businesses keep customers happy.
Reliable software isn’t just nice to have anymore but it’s something every company must deliver. Let’s explore how AI improves testing, saves time, and helps companies create better software for their users.
As we usher in a new era of digital innovation, the development of digital products continues to evolve at a rapid pace. It’s an exciting time, filled with infinite possibilities. Yet, with this progress comes increased competition and more discerning consumers. To navigate this landscape successfully, the importance of user testing and User Experience (UX) research in digital product development cannot be overstated.
We’ve already discussed what has been going on in the back-end of the Labster platform, an exciting project which glimpses into the future of education. Rollout has been helping Labster with several senior backend, frontend engineers, and QA testers (altogether 11 IT professionals). This time we share Judit’s experience, who was a member of the testing team. She played a crucial role in safeguarding the complex transition of the Labster web portal.
For life-changers: should you be trained as a junior automated software tester OR as a junior software developer The world today is in the midst
EdTech platforms are changing how we learn. But there’s one big problem: keeping students motivated to stick with online courses. That’s where game mechanics come in.
Gamification using game-like elements has quietly become a secret weapon in education. It keeps learners engaged, helps them stay longer, and most importantly, helps them remember what they learn.
Let’s break down how this works, and what’s really going on behind the scenes.
Microlearning is a modern approach to education that delivers content in short, focused bursts usually lasting just a few minutes. These bite-sized lessons are designed to teach one concept or skill at a time, making it easier to absorb and remember information. From quick videos to interactive quizzes, microlearning fits naturally into our daily routines.
This method is becoming increasingly popular in e-learning because it aligns with how people prefer to learn today on the go, in small doses, and at their own pace. In this article, we’ll explore what microlearning is, why it works, its benefits and limitations, and how it’s shaping the future of online education.
Designing student-centric EdTech is more than creating beautiful interfaces. It’s about understanding how students think, behave, and interact with technology. When UX is aligned with student needs, engagement doesn’t just improve but it transforms the learning experience. Let’s dive into the best UX practices to build EdTech that keeps students interested, active, and thriving.
The AI users are always on the lookout for smarter, faster, more intuitive tools. Yet, their first encounter with AI-driven products often leads to confusion, mistrust, or outright abandonment. Artificial Intelligence promises efficiency and personalization, but too often delivers a cold experience that pushes away the very users it aims to help.
Creating AI-powered products comes with a key challenge, how to make them smart, predictive, and scalable without losing clarity, user control, or trust. This article explores practical and strategic ways to design AI-first solutions that not only meet technical goals but also deliver experiences that truly connect with users.
About 67% of students find learning more motivating when it includes game-based elements. That’s a powerful number, and it highlights something important for everyone involved in education today. Online learning is booming, but keeping students engaged remains one of the biggest challenges. This is where gamification steps in as a strategic research-backed solution.
By 2025, the mobile learning market is expected to reach around $94.93 billion and is projected to grow to $287.17 billion by 2030, with an annual growth rate of 24.78%. With smartphones becoming more widely accessible, mobile learning (m-learning) has become an essential part of modern education.
This rapid growth reflects a shift in how people access education, making learning more flexible, interactive, and personalized. Whether it’s students looking for supplementary resources, professionals upskilling on the go, or educators seeking innovative teaching tools, mobile learning apps have revolutionized the way knowledge is shared and consumed. As technology continues to evolve, the demand for well-designed and engaging educational apps is higher than ever, shaping the future of learning across all age groups.
The world is generating approximately 402.74 million terabytes of data every single day and that’s more than all the books in every library on Earth combined, created in just 24 hours. What makes this even more fascinating is that much of this data is produced in real time, through social media posts, online transactions, IoT devices, and digital interactions. Today, real-time data is no longer optional but it’s essential for building effective digital systems.
According to the Cloud Native Computing Foundation (CNCF), Cloud-Native adoption has soared in recent years, with over 5.6 million developers using Kubernetes alone as of 2021. Leading companies like Netflix, Spotify, and Airbnb have used cloud-native approaches to power their global operations.
Just moving to the cloud isn’t enough. True success in cloud-native development comes from rethinking how software is built from the ground up. That means embracing flexible architectures, breaking apps into smaller parts that can be deployed independently, automating as much as possible, and focusing on continuous improvement. It’s not about using the cloud. It’s about using the cloud well.
In modern software development, Continuous Integration and Continuous Deployment (CI/CD) have become essential for delivering high-quality applications at speed. By automating the development pipeline, CI/CD solutions reduce manual effort, minimize errors, and enhance software reliability. These solutions help organizations scale efficiently while ensuring robust software releases. This article explores the significance of CI/CD, its key components, popular tools, best practices for implementation, and technical considerations for DevOps engineers and agencies, including advanced topics such as Infrastructure as Code (IaC), security integration, microservices deployment, and multi-cloud strategies.
Data centers keep our digital world running—everything from streaming movies to using AI tools. But they also use a lot of electricity. This can lead to big questions:
How do data centers affect the environment?
Who controls them, and why does it matter?
Can we make them more efficient and sustainable?
Gone are the days when bankers had to deal with a huge pile of paperwork, and customers at banks had to wait in long queues to get a transaction done.
All thanks to technology, which has the potential to transform banking at an exponentially faster pace.
DeepSeek has made waves in the AI industry by claiming to have trained a 671-billion-parameter model for just $6 million—a fraction of the budget typically required by industry leaders like OpenAI and Meta. To put this into perspective, Meta’s Llama 3 training required 30.8 million GPU hours, while DeepSeek achieved similar results with just 2.8 million hours. This raises an intriguing question: was this cost-saving feat driven by hardware innovations such as TPU clusters, or was it the result of sophisticated software optimizations?
The world is generating approximately 402.74 million terabytes of data every single day and that’s more than all the books in every library on Earth combined, created in just 24 hours. What makes this even more fascinating is that much of this data is produced in real time, through social media posts, online transactions, IoT devices, and digital interactions. Today, real-time data is no longer optional but it’s essential for building effective digital systems.
Most of what you know at work probably didn’t come from a training manual. Studies say roughly 75% of workplace learning happens informally just by watching, talking, and working with others. So, if we want people and teams to learn better, shouldn’t our digital platforms encourage exactly that?
EdTech platforms are changing how we learn. But there’s one big problem: keeping students motivated to stick with online courses. That’s where game mechanics come in.
Gamification using game-like elements has quietly become a secret weapon in education. It keeps learners engaged, helps them stay longer, and most importantly, helps them remember what they learn.
Let’s break down how this works, and what’s really going on behind the scenes.
Designing student-centric EdTech is more than creating beautiful interfaces. It’s about understanding how students think, behave, and interact with technology. When UX is aligned with student needs, engagement doesn’t just improve but it transforms the learning experience. Let’s dive into the best UX practices to build EdTech that keeps students interested, active, and thriving.
About 67% of students find learning more motivating when it includes game-based elements. That’s a powerful number, and it highlights something important for everyone involved in education today. Online learning is booming, but keeping students engaged remains one of the biggest challenges. This is where gamification steps in as a strategic research-backed solution.
Many enterprises struggle with outdated systems that don’t work well together. As businesses grow, they add new software and tools, but without a solid integration strategy, these systems become disconnected and difficult to manage. Traditional development often treats APIs as an afterthought, leading to slow development, high maintenance costs, and limited flexibility.
API-first development takes a different approach. Instead of building software first and figuring out integrations later, it starts with designing APIs as the foundation. This ensures that all systems, whether internal tools, customer applications, or third-party platforms, can connect smoothly from the beginning. The result? Faster development, easier system upgrades, and a more scalable, future-ready architecture.
