Welcome To Our Blog

The Demand for Generative AI: What Makes It Essential for Enterprises 

The Demand for Generative AI: What Makes It Essential for Enterprises

In 2022, Gen AI became widely known. By 2023, businesses started using it to transform various industries. Now, in 2024, this technology is set to become even more integral to our everyday lives. Researchers and companies are working on ways to seamlessly integrate generative AI into our routines. 

The Evolution of Generative AI 

Generative AI has advanced rapidly, much like the evolution of computers, but at a much faster pace. 

In the early days, only a few people had access to huge mainframe computers. These were large, expensive machines used mainly by big organizations and research institutions. Then, technology improved, and smaller, more efficient computers became available for businesses and universities. 

As time went on, these advancements led to the creation of home computers. At first, these were mainly used by hobbyists and tech enthusiasts. Eventually, personal computers became more powerful and user-friendly, making them accessible to everyone. Today, almost every household has a computer or a smartphone with incredible capabilities. 

Similarly, generative AI started as a complex technology used by a few experts. Now, it’s becoming more common and integrated into our daily lives, just like personal computers did. Researchers and companies are continuously finding new ways to make this technology useful and accessible to everyone. 

Generative AI is now in its “experimental” phase. Just like computers, it’s evolving to offer better performance in smaller packages. 

Curious how this works? 

Think about how computers were in the past. They were huge, expensive, and only a few people could use them. Now, we all have powerful computers in our pockets—our smartphones! Generative AI is on a similar path. It’s becoming more accessible and easier to use. 

Generative AI in Business Today 

Gen AI is rapidly transforming the business landscape. According to a recent McKinsey Global Survey on AI, 65% of organizations are now regularly using generative AI. This is nearly double the percentage from just ten months ago, highlighting the swift adoption of this technology. 

The expectations for generative AI’s impact are incredibly high. Three-quarters of survey respondents predict that Gen AI will bring significant or even disruptive changes to their industries. This optimism is not unfounded, as companies that have integrated generative AI into their operations are already reaping substantial benefits. 

One of the most notable advantages is cost reduction. Generative AI can automate various tasks, streamline processes, and improve efficiency, leading to significant savings. For example, it can handle customer service inquiries, generate content, and even assist in product design, all of which reduce the need for extensive human labour and cut down operational costs. 

In addition to cost savings, generative AI is also driving revenue growth. By enhancing customer experiences, personalizing marketing efforts, and optimizing supply chains, businesses can increase their sales and profitability. For instance, AI-driven insights can help companies better understand customer preferences and tailor their offerings accordingly, leading to higher customer satisfaction and loyalty. 

Did you know? Generative AI is like a secret weapon for businesses, making them more efficient and profitable. Organizations are reporting both cost savings and revenue increases thanks to this technology. It’s revolutionizing the way companies operate, providing them with a competitive edge in today’s fast-paced market. 

As generative AI continues to evolve, its integration into business practices is expected to deepen, bringing even more innovative solutions and opportunities for growth. 

Why Generative AI is So Impactful 

Several factors have made generative AI so impactful. Advanced hardware, like specialized AI chips used for training models, has enabled the creation of sophisticated models like large language models (LLMs). These tools have become mainstream due to their seamless user experience, allowing even non-technologists to engage with advanced models. 

Let’s break it down: 

  • Advanced Hardware: These are like super powerful engines that make generative AI work faster and better. 
  • User-Friendly Tools: Even if you’re not a tech expert, you can still use these tools easily. It’s like using an app on your phone—simple and intuitive. 

The Investment Boom 

The surge in interest has ignited a wave of excitement among investors. Startups taking up gen AI’s are now attracting substantial investments, as investors eagerly anticipate a revolutionary shift in business technology. 

Why are investors so excited? 

Investors are thrilled about generative AI because they see it as a groundbreaking opportunity, much like finding a hidden treasure. This technology has the potential to revolutionize various industries by automating tasks, creating new products, and enhancing efficiency. The promise of significant returns on investment is driving their eagerness to invest early and capitalize on the transformative impact generative AI could have on business and technology. 

So how is Nuvepro playing a greater Role in Advancing Generative AI 

Nuvepro is playing a significant role in advancing generative AI by focusing on upskilling and reskilling the workforce, providing hands-on training, and developing innovative AI solutions. 

Upskilling and Reskilling the Workforce 

Nuvepro recognizes the transformative potential of generative AI and is committed to equipping professionals with the necessary technical skills to thrive in this rapidly evolving field. In recent months, Nuvepro has organized a variety of hands on Gen AI workshops and hands on training sessions, enabling thousands of developers and young learners to acquire hands-on experience with generative AI. These initiatives focus on real-world scenarios, allowing participants to tackle genuine AI challenges and apply their technical skills and knowledge in meaningful ways. 

Hands-On Training Programs 

One of Nuvepro’s key strategies is to provide hands-on training that goes beyond theoretical knowledge. By engaging participants in practical exercises, Nuvepro ensures that they develop a deep understanding of Gen AI tools and techniques. This approach not only enhances their technical skills but also boosts their confidence in using AI to solve complex problems. In just the past two months, Nuvepro has successfully trained more than 1,000 professionals, showcasing its dedication to developing a highly skilled AI workforce accelerating workforce development. 

Innovative AI Solutions 

Nuvepro is also at the forefront of developing innovative AI solutions that address the needs of various industries. By leveraging generative AI, Nuvepro is creating Gen AI tools that can automate tasks, generate content, and improve efficiency across different sectors. These solutions are designed to help businesses reduce costs, increase revenues, and stay competitive in a fast-paced market. 

AI-Powered Code Generation 

Nuvepro is actively involved in the development of AI-powered code generation tools, which are revolutionizing the software development process. Tools like Amazon CodeWhisperer and GitHub Copilot can generate code snippets, speeding up the development process and minimizing mistakes. By integrating these Gen AI tools into the training programs, Nuvepro is helping developers streamline their workflows and focus on higher-level tasks. 

Continuous Learning and Adaptation 

In the rapidly changing world of AI, continuous learning is crucial. Nuvepro emphasizes the importance of staying updated with the latest advancements in AI technology. Through ongoing training and skill development programs, Nuvepro ensures that professionals are well-equipped to adapt to new tools, languages, and frameworks. This commitment to continuous learning helps individuals and organizations stay ahead of the curve and leverage AI to its fullest potential. 

Empowering the Future Workforce 

Nuvepro’s efforts in advancing generative AI are not limited to current professionals. The company is also dedicated to preparing the next generation of AI experts. By offering hands on training programs for students and young learners, Nuvepro is fostering a culture of innovation and curiosity. These initiatives aim to inspire the future workforce to explore the possibilities of AI and contribute to its development. 

Yet another main initiatives that Nuvepro has come up with is the secure sandboxes. These sandboxes provide a practical environment for hands-on learning and project-based skill development. Developers can use these sandboxes to engage with cutting-edge tools and technologies, helping them become job-ready and project-ready. 

What’s a GenAI sandbox? 

Think of it as a playground for developers. It’s a safe space where they can experiment, learn, and build without any risk. Nuvepro’s sandboxes are like the best playgrounds, filled with all the latest tools. 

Hands-On GenAI Workshops 

Nuvepro has conducted numerous Gen AI workshops focused on hands-on learning. These Gen AI hands on workshops are designed to upskill developers at different levels, from beginners to advanced professionals. Participants get to work with various Gen AI tools, gaining practical hands on experience that is crucial for workforce development. 

Why are hands-on workshops important? 

Imagine trying to learn to ride a bike just by reading a book. It’s not the same as actually getting on the bike and pedaling. Hands-on workshops give you that real experience. You learn by doing, which is the best way to understand and master new skills. 

Impressive Stats: 

  • 85% of participants in Nuvepro’s GenAI workshops successfully got upskilled. 
  • These workshops include practical hands on learning sessions using AWS Sandbox Environments, and Google Cloud Sandbox. 
  • 90% participants gained job readiness skills, and cloud-ready skills through these hands-on labs. 

Nuvepro’s other Sandbox Environments 

Nuvepro offers various sandbox environments to enhance hands on learning and skill development. These include: 

  • AWS Sandboxes by Nuvepro: These are ideal for practice tutorials, practice downloads, and hands-on labs. They help developers gain practical experience with AWS Bedrock and Amazon Q. 
  • Nuvepro’s Azure Sandboxes: These provide an Azure cloud sandbox environment for learning and practicing Azure-related projects. They are considered the best Azure sandbox to practice and gain hands-on experience. 

What’s the big deal about sandboxes? 

Sandboxes are like virtual labs where you can try out new things without any real-world consequences. They let you test, learn, and innovate safely. 

Hands-On Learning and Project-Based Learning 

Nuvepro’s approach emphasizes hands-on learning and project-based learning. This method ensures that learners not only understand the theory but also apply it in real-world scenarios. This experiential learning is essential for skill development and helps learners become job-ready/project ready. 

How does this help you? 

When you learn by doing, you remember more. It’s like learning to cook by actually making a dish instead of just reading a recipe. You gain confidence and practical skills that you can use immediately. 

Upskilling and Reskilling for Workforce Development 

Nuvepro’s initiatives in generative AI aim at upskilling and reskilling professionals. This is crucial for workforce development, as it ensures that employees have the latest skills needed in today’s fast-evolving tech landscape. 

Why is this important? 

The job market is always changing. To stay competitive, you need to keep learning new skills. Upskilling and reskilling ensure you’re ready for new opportunities and challenges. 

Nuvepro’s Impact on Job Readiness and Project Readiness 

Nuvepro’s GenAI workshops and sandbox environments are not just about learning new skills. They are about making you job-ready and project-ready. This means you not only have the skills but also the confidence to take on new roles and projects. 

Let’s take a moment: 

Imagine you’re about to start a new job or project. Wouldn’t it be great to feel fully prepared? Nuvepro’s hands-on labs and learning environments make this possible. You get real experience, so you’re ready to hit the ground running. 

Real-World Scenarios and Practical Learning 

Nuvepro’s hands-on labs and workshops are designed around real-world scenarios. This means you’re not just learning theory. You’re solving real problems, just like you would in a job. 

Why is this so effective? 

Think about learning to swim. Reading about swimming techniques is helpful, but actually getting in the water and practicing is what really teaches you. Nuvepro’s approach is similar. You learn by doing, which makes the learning experience much more effective and memorable. 

Metrics and Success Stories 

85% Success Rate: 

Nuvepro boasts an impressive 85% success rate in upskilling participants through their generative AI workshops. This high success rate is a testament to the effectiveness of their hands-on learning approach. 

Happy Participants: 

Participants in Nuvepro’s workshops often share positive feedback. They appreciate the practical, hands-on approach and the immediate applicability of what they learn. 

The Future of Generative AI with Nuvepro 

Nuvepro is committed to staying at the forefront of generative AI. They continuously update their sandboxes and workshops to include the latest technologies and best practices. This ensures that learners are always getting the most relevant and up-to-date education. 

What’s next? 

As generative AI continues to evolve, so will Nuvepro’s offerings. We are constantly exploring new ways to enhance their learning environments and provide even better experiences for their participants. 

Conclusion 

Generative AI is rapidly transforming the business world. Companies like Nuvepro are leading the way by providing practical learning environments and hands-on workshops. These initiatives are helping professionals upskill and reskill, ensuring they are ready for the jobs of the future. 

As we move forward, the integration of generative AI into everyday life will continue to grow. With tools like AWS Sandbox Environments, Azure Cloud Sandboxes, and hands-on labs, learning and development in generative AI have never been more accessible. 

Let’s embrace this exciting journey and explore the endless possibilities that generative AI offers! 

Final Thought: 

What new skills are you excited to learn? With learning resources like Nuvepro’s hands on labs, the possibilities are endless. Dive in and start exploring today! 

Sign up for Newsletter

Our Latest Posts

Job Readiness

Why Skill Validation Is the Missing Link in today’s Training programs 

In 2025, We’re Still Asking: Why Isn’t Learning Driving Performance?  Billions are being spent. Thousands of training programs are being launched every year. Yet here we are—facing a truth that’s too loud to ignore: learning isn’t translating into performance.  Let’s pause and reflect.  Have you ever completed a training, proudly received a certificate, and still felt unprepared for the real challenges at work? You’re not alone.  Despite major investments in learning platforms and certification programs, enterprises continue to face a fundamental challenge: turning learning into measurable capability. It is no longer sufficient to rely on a model where employees complete courses and organizations hope those skills translate into performance. This “train and hope” approach has crumbled in the face of increasing business complexity, fast-changing technologies, and pressure for real-time results.  Enterprises today are navigating a growing disconnect—the widening gap between upskilling and actual job readiness. While the number of training programs has increased, so has the frustration among team leads and hiring managers who realize, often too late, that employees are not ready to perform the tasks they were trained for. This gap is not just a training issue; it is a business risk.  According to Lighthouse Research & Advisory, only 16% of employees believe their skills are being developed for future success. This alarming figure comes despite organizations pouring record-breaking budgets into Learning & Development (L&D).  So where’s the disconnect? Why is the gap between learning and doing still so wide?  The High Cost of Skills Gaps  The urgency of solving this issue cannot be overstated. According to current projections, 85 million jobs may go unfilled in the next few years due to a lack of skilled talent. The estimated cost of this shortfall is a staggering $8.5 trillion in lost revenue globally. This is not a distant scenario but a rapidly approaching reality.  Surveys reveal that while a majority of organizations—around 83 percent—acknowledge having skills gaps, only 28 percent are taking effective steps to address them. The reasons behind this gap are complex, but three consistent challenges emerge across industries: visibility into real-time skill levels, mechanisms to validate whether learning has truly occurred, and the ability to act quickly based on skill readiness.  This lack of visibility, validation, and velocity is limiting the return on learning investments. More importantly, it’s hindering business agility in a world where time-to-skill is critical.  What Exactly is Skill Validation?  Let’s be clear—Skill Validation is not a buzzword anymore. It’s not just a new checkbox in the L&D strategy document.  It’s a paradigm shift—a change in how we approach talent development, assess readiness, and ensure that learning has real-world impact.  For far too long, training programs have been measured by inputs:  But the truth is, none of these guarantees job readiness.  You can complete ten courses on cloud computing and still struggle to set up a basic cloud environment. You can ace a leadership development program and still falter when managing your first real team crisis. Why? Because completing training doesn’t always equal competence.  Skill validation flips the narrative. Instead of asking:  “Did they finish the course?” We ask: Can they do the task in a real situation, or Can the person actually do the job when put in an actual project?  Skill validation helps in true learning by doing  There is a massive difference between knowledge acquisition and skill validation. It’s real practice that shows whether someone is truly ready.  Skill validation is not about learning in isolation—it’s about learning in context. It’s about immersing learners in real-life scenarios, simulated environments, and hands-on tasks that mirror the challenges they will face on the job.  What Does Skill Validation Actually Look Like?  Skill validation can take many forms, depending on the role, industry, and level of expertise. Like, for example,  In every case, the individual is not just recalling information—they’re applying it. They’re making decisions, solving problems, and adapting in real time.  This is the kind of learning that sticks. This is the kind of learning that builds confidence. And most importantly, this is the kind of learning that prepares people for the unpredictable nature of work.  Skill validation is:  It ensures your employees aren’t just trained—they’re trusted..  Why Skill Validation Is a Priority Now  The rapid advancement of technologies such as artificial intelligence, cloud computing, DevOps, and cybersecurity tools has shortened the shelf life of technical skills. Job roles are evolving so quickly that the lag between training and application can result in irrelevance. Moreover, threats such as security breaches or project failures demand instant readiness from employees, not a six-month wait to assess post-training performance.  In this context, relying solely on traditional learning models is no longer viable. Businesses need to know—immediately—whether a new hire is ready to deliver or whether an internal employee is prepared for the next level of responsibility. Skill validation addresses this need by offering evidence-based assurance of workforce capability.  Being “almost ready” isn’t enough in today’s fast-paced business landscape. Organizations need people who can deliver from day one. Project timelines are tight, customer expectations are high, and there’s little room for error.  This is why skill validation isn’t optional anymore—it’s essential.  It ensures your training efforts aren’t just about checking boxes. It ensures your workforce is not only engaged but equipped. It bridges the final and most important gap: from learning to performing.  Integrating Skill Validation Into the Learning Ecosystem  For organizations aiming to embed skill validation into their talent strategies, the approach involves three key steps:  Establishing Visibility: The first step is to identify current skill levels across roles. This requires tools that go beyond static self-assessments and instead gather real-time performance data from immersive, task-based activities.  Embedding Validation in the Learning Journey: Skill validation should not be a post-training activity. It should be integrated throughout the learning process—from initial assessments to final evaluations. This ensures that learning is anchored in outcomes, not just content completion.  Enabling Agility Through Continuous Feedback: With validated data on individual and team capabilities, organizations can respond faster—by tailoring interventions, accelerating project readiness, or rerouting resources

Read More »
Skill Taxonomy

Building a Skill Framework: Connecting the Dots Between Skills Taxonomy, Skills Ontology, Skill Families, and Skill Clusters 

In today’s fast-evolving workforce, skills have overtaken degrees and titles as the true currency of value. With emerging technologies, shifting business models, and a growing gig economy, what a person can do has become more important than what they have done. Organizations now collect immense amounts of data on employee skills through assessments, performance reviews, learning platforms, and certifications. However, most of this data sits in silos—unstructured, underutilized, and often outdated. The challenge isn’t the lack of skills data; it’s the lack of a structured way to activate it. Without a clear strategy to interpret, map, and apply this information, organizations miss out on smarter talent decisions, agile workforce planning, and meaningful upskilling paths. To truly unlock the full potential of your workforce, you need more than just a list of skills—you need a well-structured skills framework.  In this blog, we’ll walk you through how Skills Taxonomy, Skills Ontology, Skill Families, and Skill Clusters all fit together to build that structure. When used the right way, these tools can help you make sense of your skills data, close gaps, and prepare your teams for what’s next.  What Is a Skill Framework?  Imagine trying to build a house without a blueprint—or trying to manage your workforce without knowing what skills people actually have or need. That’s where a skill framework comes in.  In simple terms, a skill framework is a structured system that helps organizations identify, organize, and manage the skills of their workforce. It works like a map—clearly showing what skills are important for each role, how different skills are connected, and where the gaps are. Instead of treating skills like a random list, a skill framework brings order, clarity, and purpose to your talent strategy.  So, why does this matter?  For HR professionals, Learning & Development (L&D) teams, and talent managers, a skill framework is incredibly valuable. Without a structured view of skills, it’s hard to answer basic but important questions:  A skill framework helps answer all of these questions—and more. It becomes the foundation for smarter decisions across hiring, training, workforce planning, and career growth.  Let’s look at some of the major benefits:  First, it improves hiring. When you know exactly which skills are needed for each role, you can write better job descriptions, evaluate candidates more effectively, and reduce hiring mistakes.  Second, it enables personalized learning paths. Instead of giving everyone the same training, you can tailor learning to each employee’s current skill level and career goals. This not only boosts engagement but also speeds up skill development.  Third, it supports talent mobility. Employees often want to grow and move into new roles—but don’t always know what skills they need to get there. A skill framework shows them a clear path forward, helping them upskill and transition smoothly within the organization.  And finally, it powers better workforce planning. With a clear view of current and future skill needs, organizations can prepare ahead of time—whether that means training, hiring, or shifting roles internally.  In short, a skill framework turns scattered skills data into meaningful insights. It helps organizations not just understand their talent—but also shape it, grow it, and future-proof it.  Understanding the Building Blocks  Now that we know what a skill framework is and why it’s important, let’s break it down into its core building blocks. These are the key components that work together to give your framework structure, meaning, and power.  Think of it like constructing a building—you need a strong foundation, a blueprint, organized rooms, and proper connections. Similarly, a solid skill framework is built on four essential elements: Skills Taxonomy, Skills Ontology, Skill Families, and Skill Clusters. Each one plays a unique role in organizing and making sense of your skills data.  Let’s look at each one in simple terms:  Skills Taxonomy: Bringing Order to the Skill Chaos  One of the most important building blocks of any structured skill framework is the Skills Taxonomy. The term might sound a bit technical at first, but the idea behind it is actually quite simple—and incredibly useful.  So, what exactly is a Skills Taxonomy?  A Skills Taxonomy is a way to neatly organize all the skills in your organization into a structured hierarchy. Think of it like how you organize folders and files on your computer. You might have a main folder called “Projects,” with subfolders for each client or team, and then specific files within each one. A skills taxonomy works the same way—but instead of files, you’re organizing skills.  Here’s how it typically looks:  This kind of structure helps you create a clear, searchable, and organized list of skills across your entire workforce. It brings clarity to what skills exist, where they fit, and how they’re connected to job roles.  Why Is a Skills Taxonomy So Important?  At Nuvepro, we’ve worked with many organisations that already have skill data—but it’s often scattered, inconsistent, or duplicated. One team might call a skill “Project Management,” another calls it “Agile PM,” and a third lists “Scrum Master.” These are all connected, but without a structured system, it becomes hard to tell whether people are discussing the same thing.  This is where a skills taxonomy makes a big difference.  It gives everyone—whether it’s HR, L&D, or team leads—a common language to talk about skills. It removes guesswork and ensures everyone is aligned. When you say a role needs “Cloud Infrastructure,” it’s clear what specific skills that includes. No confusion. No miscommunication.  Making Skill Inventories Work  Suppose your organization wants to create a master inventory of employee skills. Without a taxonomy, you would likely end up with a long, unstructured list that varies from team to team. But with a skills taxonomy in place, you can organize that list in a way that’s logical and easy to manage.  Here’s what a well-structured taxonomy allows you to do:  This kind of structure makes it so much easier to:  It’s not just about organizing skills—it’s about unlocking insights from them.  Example: Building a Taxonomy for a Tech Team  Let’s say you’re

Read More »
People at Nuvepro

The Storyteller’s 3-year Journey  

Head of Marketing Shivpriya R. Sumbha, who recently completed 3 years at Nuvepro, looks back on her journey with grace, grit, and gratitude.  Questions curated by Anisha Sreenivasan 1. How has your journey at Nuvepro been since April 2022? Any moments that stand out as turning points or proud achievements?  Thanks, Anisha, for kickstarting the #PeopleAtNuvepro series—such a great way to reflect and share!  Since joining in April 2022, the journey’s been full of learning, growth, and quite a few “wow, we’re really doing this” moments. We’ve evolved so much—not just in what we offer, but how we think about the value we bring to the table.  There’ve been many initiatives that we’ve worked on, but for me, the proudest moments are when customers describe us not just for what we do, but for what we enable. When they see Nuvepro as a go-to for project readiness and skill validation—not just as a tool or a platform or divide our offerings and know us for 1 of it,  but as a true enabler of Project Readiness – When they get that without us having to spell it out—it feels like we’re doing something truly right. That kind of recognition hits differently. 2. You’ve played a huge role beyond just Marketing Campaigns, workshops, hackathons, even sales outreach. How do you manage to juggle it all so well?  Honestly, I don’t think it ever feels like we’ve “figured it all out”—and maybe that’s a good thing. There’s always more we can do, more ideas we haven’t explored yet, and that’s what keeps it exciting. We’ve done some great work as a team, no doubt, but I still feel like we’re only scratching the surface of what’s possible.  Marketing, especially in a tech-driven company like ours, often plays the role of the silent enabler. Most of the spotlight naturally goes to the tech—and rightfully so—but behind the scenes, it’s been amazing to see how strategic marketing efforts have quietly shaped the brand, created visibility, and opened doors we didn’t even know existed.  What I really hope to see in the coming days is Nuvepro being recognised not just for what we build, but how we’re building a brand that resonates—with customers, partners, and even within the team. We, are often attributed by the tech we create and not the way the brand has been overseen by the marketing efforts. Hopefully, we’ll see that day soon, too.   3. What was the most memorable event you worked on at Nuvepro-and what made it special? Of course, the first Nuvepro Project Readiness event was a huge success, and we all know it. That goes out to be my most memorable, and not because it was the first or because of the efforts put in. I was happy to know that the internal teams and management now know about the power of such event marketing strategies and how evidently they can bring us good connections. Striking that chord of confidence will always remain memorable.   4. As someone who built the marketing function from scratch here, what were your biggest challenges and learnings in the process? Initially the biggest hurdle was defining what marketing should look like in an enablement-driven, tech-first environment. There wasn’t a rulebook to follow—we had to experiment every few days on how we wish to be pursued.   One of the key learnings was that marketing doesn’t have to be loud to be powerful all the time. Most of the brands and projects that I had worked for were on unmatchable performance marketing budgets but with Nuvepro I learnt that sometimes, the most impactful work happens in the background—crafting the right narrative, building relationships, or simply bringing organic consistency to how the brand shows up. It took time to shift perceptions—from seeing marketing as just promotion to recognizing it as a slow go-getter. It has made me learn about the organic growths too which are often overlooked in Marketing.   5. You have hosted several workshops, hackathons and roundtable conferences. What excites you most about these events?  I guess connects and the post-event relationships that we build. We can simply set up a sales campaign or a PPC campaign and write sales ad copy, but we believe meeting someone and talking to someone establishes a much stronger relationship, and we aim to do just that. That excites me the most. The ability to network and build relationships through these events is truly good.  6. Beyond work, what are your go-to ways to unwind or recharge after a packed day of marketing magic?  Now, since life has changed a bit, I like to read less, watch cricket a little less, stream less and indulge more in other things like #apartmenttherapy as you may call. I try out multiple recipes, I garden a lot more, I clean a lot more and learn many more things that I had never tried before. I always did all this before, too, now, with a unique zest. It is therapeutic for me to be a house runner; I love it, and I don’t wish it any other way.    7. Looking back at your journey from 2022 to now, what’s one piece of advice you’d give your past self?  Haha just this one, “Your manager is a really good human first, and you will learn a lot, and you will have a great time in the coming few years, make the most of it, trust the process, don’t think you will not be able to survive 😊 ‘’   8. You’re always full of energy as your colleague’s mention-how do you do that? At a very early point of time in life I have realized, our happiness and mood is our own responsibility, So I TRY to be not very much affected by the external factors, people, challenges and try to be in the best of moods always and the other thing is obviously, I love the idea of being approachable and friendly as a person. I obviously only try.   9. And

Read More »
Categories