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83% Success Rate: How Our GenAI’s Hands-On Learning Workshop Prepared Developers for Real-World Challenges 

Project readiness, IT job readiness, Job readiness, Hands-on learning

The Buzz Around GenAI 

Generative AI, or GenAI, is the latest buzzword reverberating through the tech industry. It’s a topic on everyone’s lips, from developers and software professionals to entire tech organizations. The rise of generative AI has caused quite a commotion, and not without reason. While some professionals—about 35%—are worried about the potential impact on their jobs, another 17% are curious about its capabilities and applications. However, the majority see GenAI as a beneficial tool that can promote workforce development by enhancing their technical skills and expanding their abilities. But for many of us, understanding and using GenAI isn’t just about theory; it’s about getting our hands dirty and actually building something. At Nuvepro, we’ve seen this firsthand, especially during our recent GenAI hands-on workshop in partnership with AWS. For those apprehensive professionals, there’s an essential lesson: hands-on learning can unlock more potential than they ever imagined. 

Too Much Theory, Too Little Practice? 

If you’ve ever tried to learn a new technical skill, you know how overwhelming it can be. The internet is overflowing with resources—tutorials, YouTube videos, and MOOCs—but how much do you really absorb by just reading or watching? The real learning happens when you dive in and start doing it yourself. At Nuvepro, we recognized this gap. We noticed that while many workshops focus on theoretical knowledge, they often fall short on practical application. This realization led us to change our approach. 

Our GenAI Workshop: A New Approach 

We recently conducted our first GenAI hands-on workshop learning session in partnership with AWS, and it was a game-changer. The idea was simple: take developers through a journey where they could actively engage with the technology. Over 80 participants joined us, and the energy in the room was electric. The task? Build an app to analyze weather data using Amazon Q. 

The Challenge: Building an App with Amazon QD 

Participants from esteemed universities and developers from  top companies like Tata Consultancy Services, Virtusa, Tech Mahindra, Capgemini, Rakuten, etc had been a part of our GenAI workshop. Everyone had their laptops out, ready to tackle the challenge. The goal was to use Amazon Q, leveraging its powerful CodeWhisperer functionality to generate code. Participants had to cleanse data using Python libraries, render it graphically, and provide user controls for visualization—all by prompting Q to generate the necessary code. It was intense, it was practical, and it was exactly what we needed. 

The Magic of Hands-On Learning 

There’s something incredibly satisfying about seeing your code come to life. During the GenAI hands on workshop, participants weren’t just passively following along; they were actively solving problems, debugging issues, and learning by doing. The moment when someone finally gets their app to work, the look of accomplishment is priceless. That’s the magic of hands-on learning—it sticks with you in a way that theory alone never can. 

Real-World Skills for Real-World Challenges 

The focus on hands-on learning isn’t just about building an app; it’s about preparing for real-world challenges. GenAI is set to become a fundamental part of the tech industry, and the demand for skilled professionals is only going to grow. By engaging in practical exercises, developers gain insights that are directly applicable to their jobs. They learn how to navigate complexities, troubleshoot issues, and think critically—skills that are essential in today’s tech landscape. 

Innovations at Nuvepro: GenAI sandboxes and Guided Projects 

To make this kind of learning accessible, we’ve introduced innovative solutions through our hands-on labs like GenAI sandboxes, and guided projects. 

Guided Projects: Taking Learning to the Next Level 

Once you’ve got the basics down, it’s time to tackle more complex challenges. Our GenAI sandboxes and guided projects are designed to help you apply what you’ve learned in meaningful ways. For example, you can use Amazon Q to write a chat application from scratch or improve an existing language model by writing better prompts or fine-tuning it with Retrieval-Augmented Generation (RAG). These real world guided projects push the learners to think creatively and develop solutions that have real-world applications. 

GenAI sandboxes: Safe Spaces to Experiment 

Have you ever watched a video about how Amazon Q (CodeWhisperer) can be used to generate a new function? Why just watch when you can use our hands on labs? Our GenAI sandboxes are preconfigured environments where you can experiment with GenAI tools like Amazon Q without worrying about making mistakes. These sandboxes for AWS Bedrock and sandboxes for Q developer (CodeWhisperer) come with budget and service limits, ensuring a safe and controlled setting for learning. You can explore, test, and refine your skills with confidence. 

Leveraging AWS Bedrock and Amazon Q – GenAI sandboxes 

At Nuvepro, our hands-on learning solutions are powered by AWS Bedrock and Amazon Q. These tools are at the forefront of GenAI technology, offering robust features and capabilities. 

AWS Bedrock: A Comprehensive GenAI Platform 

Amazon Bedrock provides all the foundational capabilities needed to consume, fine-tune, deploy, and operationalize GenAI models. It’s secure by design, with data staying within the customer environment and no data used for retraining. Bedrock’s serverless architecture means you don’t have to worry about provisioning infrastructure or scaling—Amazon handles the heavy lifting. It’s customizable, allowing you to fine-tune models to suit your specific needs, and it integrates seamlessly with the AWS ecosystem. 

GenAI sandboxes for Amazon Q 

Amazon Q  is a game-changer for developers. It generates code based on natural language prompts, making it easier to build applications quickly. During our workshop, participants used CodeWhisperer to generate Python code for data cleansing and visualization. It was a powerful demonstration of how GenAI can streamline development processes and enhance productivity. 

Leveraging GenAI Sandboxes in Amazon Bedrock and Q Developer (CodeWhisperer) for Enhanced Learning and Innovation 

Hands-on experience and experimentation are crucial for mastering new technologies. GenAI Sandboxes offer a unique and powerful way to facilitate this learning process, providing safe and isolated environments where users can test and refine their technical skills without the risk of affecting live systems. At our recent GenAI workshop, we highlighted the transformative potential of sandboxes in two key areas: sandboxes for Amazon Bedrock and sandboxes for Q Developer (CodeWhisperer). 

Sandboxes for Amazon Bedrock 

Amazon Bedrock is a comprehensive platform that enables users to consume, fine-tune, deploy, and operationalize generative AI models. Its robust features include foundational capabilities, secure by design architecture, serverless operation, customization options, extensibility with the AWS ecosystem, and accessibility for all user personas. One of the standout features of Amazon Bedrock is its sandbox environment. 

How Sandboxes for Amazon Bedrock will Help Learners 

Experimentation and Innovation: The GenAI sandboxes for Amazon Bedrock allows learners to experiment with different AI models and configurations without the risk of disrupting production environments. This freedom fosters innovation as users can test new ideas and approaches in a safe setting. 

Learning and Skill Development: For new learners, Nuvepro’s GenAI sandboxes provide a practical learning space to understand the intricacies of Amazon Bedrock. They can practice fine-tuning models, integrating with AWS services, and deploying applications, which accelerates their learning curve. 

Cost Efficiency: As the GenAI sandbox environment is serverless and incurs no costs, learners can explore and develop without worrying about financial implications. This cost-effective approach is particularly beneficial for startups and educational institutions with limited budgets. 

Customization and Adaptation: Learners can fine-tune models in the GenAI sandbox to better align with their specific data and domain requirements. This customization ensures that when they move to production, their models are optimized for their unique needs. 

Operational Readiness: By simulating deployment scenarios in the GenAI sandbox, learners can anticipate and address potential issues before they arise in a live environment. This proactive approach enhances operational readiness and reduces the risk of downtime. 

Sandboxes for Q Developer (CodeWhisperer) 

Q Developer, powered by Amazon CodeWhisperer, is another pivotal tool in the generative AI toolkit. CodeWhisperer assists developers by providing AI-driven code suggestions, which streamline the coding process and enhance productivity. The sandbox environment for Q Developer amplifies these benefits, making it an invaluable resource for both novice and experienced developers. 

How Sandboxes for Q Developer (Sandboxes for codewhisperer) will Help Learners 

Skill Enhancement: GenAI Sandboxes for codewhisperer offer developers a risk-free space to practice using CodeWhisperer. They can experiment with different coding scenarios and receive AI-generated suggestions, which helps them understand how to leverage AI to improve their coding skills. 

Accelerated Learning: For learners, the GenAI sandbox environment provides immediate feedback on their coding attempts. This iterative learning process helps them quickly grasp the nuances of coding with AI assistance, thereby speeding up their mastery of the tool. 

Error-Free Development: By testing their code in a sandbox, developers can identify and correct errors before deploying their applications. This error-free approach ensures that when the code moves to production, it is robust and reliable. 

Collaboration and Sharing: Nuvepro’s GenAI Sandboxes for codewhisperer enable developers to collaborate on real world projects by sharing their sandbox environments. This collaborative approach fosters a community of practice where developers can learn from each other and collectively enhance their technical skills. 

Innovative Solutions: The freedom to experiment in Nuvepro’s GenAI sandboxes encourages developers to think creatively and develop innovative solutions. They can try out new coding techniques and integrations with other AWS services, which can lead to groundbreaking applications and services. 

The Impact: Building Confidence and Competence 

The response to our workshop was overwhelmingly positive. Participants from some of the most renowned enterprises were not only engaged but also excited about the possibilities of GenAI. They left with a deeper understanding of how to apply these tools in their own projects and a newfound confidence in their skills. 

A New Way Forward 

The success of our GenAI hands-on workshop is a clear indication that this is the way forward. As GenAI continues to evolve, the need for practical, experiential learning will only increase. At Nuvepro, we’re committed to providing these opportunities and ensuring that developers are equipped to meet the challenges of the future. 

Conclusion: Join the Hands-On Revolution 

If you’re a developer or tech professional looking to upskill, don’t settle for theory alone. Dive into hands-on learning with Nuvepro. Our hands on learning workshops on our hands on labs through our secure sandboxes for AWS Bedrock/ sandboxes for Q developer (CodeWhisperer) are designed to give you the practical experience you need to succeed. GenAI is the future, and with the right skills, you can be a part of it. Join us on this journey and unlock your full potential. 

In a world where technology is constantly changing, staying ahead means not just knowing about the latest advancements, but being able to use them. Hands-on learning is the key, and at Nuvepro, we’re here to make sure you have the tools and support you need to thrive. 

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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

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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

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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

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