Whether a state or local government, or a U.S. government agency, a major problem facing government and industry alike is their aging mainframe systems. A shrinking workforce with experience in older languages such as COBOL, limits the ability of organizations to maintain these legacy systems and prepare for the future. This was apparent as states like New Jersey, facing strain on their systems during the early days battling COVID, called for assistance with their COBOL systems.
Now as federal agencies seek new opportunities to introduce efficiencies via artificial intelligence (AI), these systems provide an easy target for modernization. AI with its ability to tackle complex, repetitive tasks accurately provides one solution to the government mainframe modernization challenge.
To this end, our Karsun Innovation Center experts devoted their time to producing a complete suite of AI solutions dedicated to tackling the mainframe modernization challenge.
The COBOL Modernization Challenge
With their decades-old interconnected applications and systems, these legacy mainframe systems are complex, expensive to maintain, difficult to change, and vulnerable to attacks. At the same time, the cloud presents the opportunity to build secure, resilient systems that adapt to the changing needs of its users.
Past modernization and migration attempts appeared out of reach for these systems. Stymied by both the cost and time required to transform these systems. These high-value assets handling mission-critical workloads present a high stakes challenge for modernization teams. Often core to the business with large customer bases, they have vast complex functionality that must be broken down into smaller parts before proceeding.
Karsun applied AI, speeding up this tedious task while ensuring modernization teams had a complete map of the legacy system. Using its ReDuX platform, Karsun limited the impact of poorly documented systems and unanticipated relationships between components. When integrated with the other tools available in the ReDuX platform, AI-assisted teams generated production ready code two times faster than when they used humans alone.
Further given this complexity, some organizations may decide to simply replatform the system. But AI gives us the opportunity to do more than lifting and shifting the application to the cloud. It empowers us to optimize with a product mindset. With this in mind we can build human centered systems that scale and adapt to a changing environment.
The Solution: AI for Mainframe Modernization
Enter ReDuX, Karsun’s AI-powered digital transformation platform. We built our platform using AI to accelerate modernization while reducing risk. Using Amazon Bedrock, a platform that provides access to AI tools via an API, Karsun built a comprehensive digital transformation platform. Karsun’s ReDuX provides AI-enhanced tools for modernization team members from designers to developers in a single platform.
Using generative AI, the platform creates a complete blueprint of a legacy system, reducing risk, and generates behavioral insights. Using this information business analysts, designers, and others do more than rewrite these legacy systems, they reimagine an optimized system designed to match the needs of its users.
This product oriented process is enhanced throughout the modernization effort via the platform’s digital transformation agents. Using agentic AI, the modernization team can chat with their code for deeper understanding and apply reusable templates using automations to rapidly scale their work while reducing risk.
ReDux is already in use by the Karsun teams delivering large-scaled complex modernization solutions to our federal agency customers. We recently shared our experience on the AWS Public Sector Blog. To learn more about AI Solutions for government modernization visit us here: https://karsun-llc.com/solutions/artificial-intelligence-ai-solutions/
Stuck with a difficult modernization challenge? Check out GoReDuX.AI and get unstuck today!
With National Data Privacy Week upon us, we reflect on the shifting data environment. From concerns surrounding artificial intelligence (AI) to an evolving threat environment, there is as great a need as ever to be mindful in our approach to protecting data. Our Karsun Innovation Center experts have met this challenge producing new solutions to address future requirements.
Our teams have a long history of incorporating emerging technologies into our data solutions. We build data platforms that produce meaningful insight while protecting sensitive data. Whether that occurs through machine learning (ML) for business intelligence or incorporating well-architected practices into our data-led migration. Moreover, many of these novel solutions incorporate machine learning and AI to further enhance data privacy.
Utilizing Synthetic Data
Synthetic data enables enterprise data teams to innovate securely. This data is produced through machine learning using models that learn the patterns, structures, and relationships within the real dataset. Next, artificial, or synthetic, data is produced with similar statistical properties to the original data set. Thus, this process masks sensitive data, such as personally identifiable information (PII).
By providing high-quality datasets that mirror real-world data without exposing this data, synthetic data minimizes privacy risks, supports compliance with regulations like HIPAA, and reduces the impact of data breaches. Meanwhile, by allowing safe data sharing and model training, synthetic data accelerates AI and analytics development while ensuring ethical data practices, making it a powerful tool for balancing privacy and innovation. Introducing strong synthetic data practices can be one of the steps organizations can take to prepare their data for an AI-enhanced future.
Security Automation
We can apply both predictive AI and generative AI (GenAI) and enhance organizations’ security posture by strengthening their security automation. While predictive AI identifies threats, GenAI creates new pathways to addressing security concerns. GenAI is particularly well suited to automating security. When incorporated into an AI-powered platform, it enhances safety culture by applying guardrails, best practice policies, templates, and automations that proactively address security concerns. GenAI further enhances security through its self-healing mechanisms that assess threats and then incorporate those assessments into its policy recommendations.
GenAI to Meet Regulatory Requirements
GenAI also offers significant potential for meeting regulatory requirements as modernization teams migrate legacy systems. We have written about this extensively on the ReDuX website. ReDuX is our AI-powered platform that accelerates mainframe modernization. One component of that platform is a mapping feature that builds a blueprint of the legacy system. With an enhanced understanding of the legacy system, the team avoids security pitfalls, identifying functional code while removing dangerous dead code and reducing the risks and errors. Moreover, using a platform with built resources allows teams to introduce guardrails like those used to improve security automation.
Bringing It Together
Consider then a data project where each of these methodologies is included as part of a robust data practice. First, synthetic data is produced using machine learning. When combined with AI-assisted development, like that used by ReDuX, the security automation guardrails enforced by the AI-powered platform ensure proper security tools and practices, including those applied to synthetic data, are used properly every time. Then, as AI practices evolve, they are refined further.
AI/ML helps technology teams navigate complex regulatory landscapes, including compliance with standards like HIPAA, FISMA, and GDPR, to ensure data privacy and system security. By adopting an AI-enhanced approach, agencies can protect privacy, overcome regulatory challenges, and maintain secure and resilient applications to align with their data goals. To learn more about emerging technology from the Innovation Center, visit our Projects Page or take the first step on your data modernization journey and connect with us on our Data Solutions Page.
This summer, our Karsun Innovation Center was filled with excitement as our intern cohort tackled AI research and development projects. These talented students addressed real-world challenges and contributed to our cutting-edge AI toolkits and resources. As we conclude 2024, we highlight below the exceptional work done by our interns, with a focus on their projects and the skills they honed while with our modernization experts.
Embracing Real-World Challenges
From their first day in our Herndon, Virginia offices, our interns were exposed to complex problems that demanded innovative solutions. Namrata Hari, a Computational Modeling and Data Analytics student, applied her knowledge to develop a task management application using Java Spring Boot and React. Her project prepared her team for upcoming tasks and equipped them to handle the intricacies of modern software development. Namrata’s primary focus during her AI internship was on testing ReDuX, a toolkit for AI-accelerated modernization. She and her team assessed memory, user interface, and overall user experiences, identifying and addressing defects to improve the AI bot’s functionality.
Pioneering AI Solutions with ReDuX AI
Another inspiring story comes from Samhita Kumar, a rising sophomore at Yale University. Samhita leveraged the ReDuX toolkit for her projects, particularly the AI code generation capabilities included in AppPilot. She combined various tools—Java Spring Boot, PostgreSQL, Podman, and React, among others—to build full-stack projects and refine her understanding of AI applications. Her work involved proposing enhancements to ReDuX and resolving defects within the AppPilot’s frontend design. Samhita’s contributions are an excellent example of AI internships at the Karsun Innovation Center pushing the boundaries of modern software development.
Enhancing User Experience through Full-Stack Development
Manojdeep Dakavaram‘s internship was a blend of full-stack development and problem-solving. A master’s student in computer science, he worked on multiple projects, including a centralized task management system and automating user access to Karsun’s O’Reilly virtual training library. His efforts improved user experiences by addressing critical bug fixes and developing new features in the React front end of AppPilot. Manojdeep’s work showcased the powerful impact of meticulous development and technology integration.
Data Management and Visualization Innovations
Pravalika Gollapudi, a Master’s student at Arizona State University, concentrated on data management and dashboards. She developed a CRUD application and a React dashboard, which streamlined data interactions and improved presentation reliability through rigorous testing. Pravalika’s role also involved conducting data quality analysis, ensuring data integrity and reliability. Her projects underscored the pivotal role data plays in modern AI and software systems.
Automation and Streamlined Workflows
The importance of automation and workflow optimization was highlighted by Visvajit Murali’s contributions. A student from the University of Virginia, Visvajit utilized technologies like PostgreSQL, Spring Boot, and Docker to automate tedious tasks, enhancing user experiences and system efficiency. His work illustrated how automating repetitive tasks can drive productivity and innovation.
Advancing with Generative AI
Generative AI continues to be a game-changer in the tech industry, as evidenced by the work of our interns and our ReDuX mainframe modernization team. The Karsun Innovation Center challenged these students to explore and propose enhancements to our AI toolkits. This focus on generative AI was epitomized by their efforts in developing and refining AI-driven code generation tools, which promise to accelerate and streamline modernization processes effectively.
Lessons and Growth from Internship Experiences
The professional growth of our interns was significantly influenced by their experiences at the Karsun Innovation Center. Daily interactions with seasoned experts, regular “Show Don’t Tell” meetings, and hands-on projects provided them with invaluable industry insights. Interns like Namrata and Manojdeep highlighted the benefits of a collaborative and supportive environment, while others, such as Pravalika and Visvajit, emphasized the importance of continuous learning and adaptability.
This summer, our interns at the Karsun Innovation Center not only contributed to the development of AI solutions but also grew as professionals poised to lead the next wave of innovation. Their stories serve as testaments to the power of immersive learning and the impact of forward-thinking, supportive mentorship. As we look ahead, we are excited to see how these budding experts will shape the world of AI and technology. Check out our Innovation Center Projects to learn more about ReDuX and other emerging technology projects from our research and development team.
For many organizations, an Amazon Web Services (AWS) Competency is table stakes. In fact, Canalys released a report revealing that organizations with AWS Specializations, including competencies, unlock $315 billion in customer spending. Moreover, 87% of customers surveyed ranked specializations among the top three selection criteria. For the Amazon Partner Network (APN) partners that achieve these designations, it signifies their expertise, commitment to industry best practices, and ability to deliver solutions seamlessly on AWS. For competency partners, it also presents new opportunities to leverage AWS resources to empower their customers as they migrate to the cloud and accelerate technology adoption.
Migration Incentives
An AWS Competency more than differentiates partners based on their expertise and experience. It also opens up new opportunities to support customer modernization efforts. A 2022 Canalys Partner Ecosystem Multiplier study found that for every dollar of AWS infrastructure sold, there is up to $6.40 available to partners to deliver services to customers.
For example, Karsun achieved its AWS Migration Competency in 2021. As a result of this designation, Karsun teams could use AWS Migration Acceleration Program (MAP) resources. This comprehensive program packages best practices, tools, expertise, and financial incentives to make cloud adoption easier. When applicable, Karsun implements these financial incentives as part of its Cloud Runways toolkit, which accelerates cloud migration through fit-to-purpose transformation playbooks. These enable incremental migrations that adapt to unique customer requirements and constraints.
Technology Acceleration
A government information technology contractor with more than a decade of experience serving U.S. government agencies, Karsun achieved its Government Competency status in 2019. The competency differentiates AWS Partner Network (APN) members serving government agencies with deep domain expertise in security and compliance, in addition to innovative cloud solutions that leverage AWS services.
In a recent video, Karsun Innovation Center Senior Vice President Badri Sriraman shares his experience integrating emerging technology with the resources available to AWS government competency partners. Filmed at the AWS Washington, D.C. Summit Government Competency Leadership Circle, Sriraman discusses how his team used tools from AWS to accelerate Karsun’s AI toolkit, ReDuX AI. Powered by AWS Bedrock, ReDuX AI uses analysis generative AI to perform code analysis, provide recommendations, and generate code for teams working on mainframe modernization projects. To learn more about ReDuX AI, visit GoReDuX.AI.
In addition to migration and technology benefits, competency partners have access to specialized training, industry events, and support from AWS experts. Partners with AWS Specializations have a wealth of opportunities to support their customers’ modernization ambitions. Overall, the partners that have obtained AWS Competencies significantly enhanced their ability to deliver high-quality AWS solutions.
Karsun is among those partners using the full range of resources available to it as it serves its agency customers. It elevates agency capabilities through modern software development, cloud, data, and AI solutions. Its cloud portfolio offers a full suite of solutions, including hybrid architecture, platform buildout, and application migration. It has AWS Government, Migration, and DevOps Competencies and is a Well-Architected Partner. To dive into Karsun’s complete cloud solutions portfolio, visit https://karsun-llc.com/solutions/cloud-solutions/.
Our Karsun Innovation Center (KIC) Interns explore complex modernization problems, experiment with emerging technology such as artificial intelligence (AI), and engage with experts on our research and development team. Every summer, we feature our interns’ work on the Karsun website. In this interview, Computer Science student Samhita Kumar shares her experience with the AI code pairing tools included in Karsun’s ReDuX AI, front-end design using component libraries, and task management automation.
Finding Her Next: Software Development, Cryptography and AI Innovation
First, please tell us about yourself. Where are you going to school? What are you studying? What do you like to do in your free time?
Samhita: I’m Samhita, a rising sophomore at Yale University studying computer science. In my free time, I enjoy reading, visiting museums, and baking. I’m also part of my school’s moot court team and love learning about Constitutional law.
What do you want to do after this internship? What are your career goals?
Samhita: I hope to build on the skills I’ve acquired while here, and to apply my knowledge to real-world problems. I aim to pursue opportunities in software development and cryptography, and to continue working with new innovations like ReDuX.
Full Stack Development and Generative AI
Karsun’s ReDuX AI uses generative AI to make code, data, and access control recommendations. In addition to their work exploring the use of AI for modern software development, we also challenged our interns to identify and propose enhancements to our AI toolkits. Samhita applied her full stack development skills to this challenge.
Could you share a little bit about the project you worked on as part of this internship? What challenge does it solve? What technologies and tools are you using?
Samhita: I have primarily been working with KIC’s ReDuX AI code pair tool, AppPilot. I used Java SpringBoot, PostgreSQL, Podman, Testcontainers, Nx, React, and Jest to build a full-stack project while testing AppPilot. My front-end design pulled in several component libraries such as Metrostar Comet. I also created a Task Manager project with CRUD functionality and user accounts to strengthen my understanding of the technology stack. Finally, I helped find and resolve defects within AppPilot.
Flexibility, Adaptability, and Innovation
What is your favorite part about working with the Karsun Innovation Center? Is there a weekly meeting or ritual you enjoy? The opportunity to learn more or get a new certification?
During our biweekly “Show, Don’t Tell” meetings, I’ve been able to learn about the projects that the Karsun Innovation Center is working on. It has been amazing to explore so many different technologies and to see the different approaches that can be taken to address blockers.
What is your biggest takeaway from your experience as an intern at Karsun?
It is definitely the importance of flexibility. I’ve gained so much practical experience and observed how unexpected issues can arise at any moment. To tackle these challenges, I learned to remain adaptable and prepared for anything. This approach has proven incredibly helpful, and it’s one I will definitely carry forward in my career.
Samhita worked alongside Karsun Innovation Center experts throughout her internship program. Discover how Karsun experts are modernizing for every next in our Innovation Center by accelerating transformation with the ReDuX AI toolkit.
Our Karsun Innovation Center hosts future technology experts every summer for our annual internship program. Computational Modeling and Data Analytics student Namrata Hari joined this year’s class to advance her data science skills while diving into complex, innovative projects. In this interview, she shares her experience in the Innovation Center environment, contributing to center projects and uncovering her path to finding her next.
Finding Her Next: Data Science to Social Impact
First please tell us about yourself. Where are you going to school? What are you studying? What do you like to do in your free time?
Namrata: Hi, I am Namrata! I am a rising sophomore studying Computational Modeling and Data Analytics at Virginia Tech, with a minor in Computer Science and Mathematics. During my free time, I enjoy dancing, singing, and watching movies.
What do you want to do after this internship? What are your career goals?
Namrata: After completing this internship, I aim to participate in professional events and conferences to enhance and sustain my networking skills. My career aspiration is to become a data scientist focusing on complex data projects that extract valuable insights and foster social impact.
Building the Future of AI Accelerated Modernization
In addition to researching and developing solutions with emerging technologies, the Karsun Innovation Center builds toolkits for our teams using these evolving solutions, industry best practices and under guidance from industry experts. One of these toolkits is ReDuX AI, a set of tools and practices for AI accelerated modernization. As part of her internship, Namrata worked with the team developing future enhancements to this toolkit.
Could you share a little bit about the project you worked on as part of this internship? What challenge does it solve? What technologies and tools are you using?
Namrata: Throughout the initial weeks of the internship, I focused on developing a task management application using Java Spring Boot and React. This project has been valuable in preparing us for upcoming tasks.
Namrata: The primary focus of my work during this internship has been testing ReDuX AI. Working within teams, we were assigned stories to complete through the use of AppPilot. During this project, we utilized Nx, Spring Boot, Postgres, Flyway, Podman, React, Comet, and Jest. Throughout this process, we were able to assess the memory, user interface, and overall user experience of the AI bot. Upon completing this project, we began addressing the defects we had previously identified.
The Innovation Center Environment
What is your favorite part about working with the Karsun Innovation Center? Is there a weekly meeting or ritual you enjoy? The opportunity to learn more or get a new certification?
Namrata: My favorite part about working with KIC is the supportive environment that I am constantly surrounded by. I enjoy seeing the work done on the projects I always hear about during our daily stand-up meetings in Show Don’t Tell. The questions asked during Show Don’t Tell helped me learn and develop my skills by showing me what questions should be asked and how to answer them. I appreciate being in an environment where I can always learn something new, no matter what.
What is your biggest takeaway from your experience as an intern at Karsun?
Namrata: My biggest takeaway from my experience at Karsun is understanding industry dynamics. I had the opportunity to gain first-hand exposure to the inner workings of the field, including observing how various challenges are tackled and identifying best practices. This experience has been instrumental in expanding my knowledge and expertise in the industry and has significantly contributed to my professional growth and development.
Namrata worked alongside Karsun Innovation Center experts throughout her internship program. Discover how Karsun experts are modernizing for every next in our Innovation Center, among our data solutions teams, and as they use our ReDuX AI toolkit.
Recording live from the AWS Summit Washington, D.C., Karsun’s Badri Sriraman sits down with John Gilroy and the Federal Tech Podcast to discuss all things AI, accelerating legacy systems modernization and hyperlocal contextualization. Badri is the Vice President of the Karsun Innovation Center. Here, teams work to eliminate or reduce friction for the agencies modernizing their legacy systems. As part of that work, they developed ReDuX AI, a toolkit using AI resources to address common issues related to modernizing these older, more complex legacy systems. Throughout the interview, Badri and John discuss the costs and security risks associated with staying on current systems and the opportunity for AI to provide insight through hyperlocal contextualization to tackle these challenges.
Addressing the O&M Problem
The interview begins by acknowledging the drag aging infrastructure has on these agencies’ enterprise systems. The issue becomes intractable when operations and maintenance (O&M) costs become so high they take up the budget that would otherwise be used for modernization and systems enhancements. A 2023 Government Accountability Office (GAO) report examined the 10 critical systems it identified most in need of modernization. Some of those systems were over 50 years old and, in total, cost the government upwards of $337 million annually to operate and maintain.
In addition to the O&M costs, complex relationships between different systems components, older programming languages like COBOL, and outdated documentation all contribute to the difficulty of modernizing mission-critical legacy systems like those studied. As Badri reveals in the interview, artificial intelligence (AI) can be used to address many of those concerns. Moreover, those same AI tools may accelerate the transition, further reducing O&M costs as agencies move away from these legacy systems.
Eating the Elephant
In the interview, Badri shares a key component of Karsun’s AI-accelerated modernization methodology, hyperlocal contextualization. In a traditional modernization project, teams typically take an incremental approach. To “eat the elephant,” teams go one step at a time, optimizing as they modernize to reduce costs. The analysis required to peel away each part of the legacy system could slow down modernization to a yearslong process in highly complex systems. Throughout the process, these teams must untangle how different parts of the system integrate and work together.
Alternatively, using AI teams still move incrementally, avoiding the pitfalls of Big Bang Modernization. However, they also use AI to identify and map these relationships within legacy systems. This AI assistance helps those teams move at a rapid pace. Working together with the human team and stakeholders, the AI can quickly create a fuller understanding of the system, its impact on the mission and provide new insights into optimization opportunities during the modernization process. This analysis is the first step in using AI for hyperlocal contextualization.
The Security Imperative
An equally pressing concern is rising security threats. The 2023 GAO report found among the chief concerns for these aging systems were outdated hardware and security vulnerabilities. The same processes that help modernization teams optimize to reduce O&M costs can also be used to move from less secure systems to more secure systems based on industry standards and best practices.
Jumping in with Hyperlocal Contextualization
With more advanced large language models (LLMs), AI tools cannot only write the code but also review, debug, and make recommendations. Powered by AWS Bedrock, ReDuX AI not only takes the insights from its eat the elephant analysis but also makes recommendations to Karsun developers using the context generated from those insights. Plus it can then incorporate best practices and security policies into those recommendations. Using a tool like ReDuX AI, the security optimization recommendations are customized to the complexities found in that legacy system, resulting in a modernization process designed to optimize costs and security. Badri discusses this hyperlocal contextualization in greater depth in the interview.
The future is bright. In a 2019 report, the GAO shared agencies provided 94 examples of successful modernization initiatives over the five years studied. While some of the most challenging projects remain, AI tools, like those used by ReDuX, create a future where the remaining mission-critical systems modernize a possibility. Check out the full interview at www.theoakmontgroupllc.com/ep-161-how-to-overcome-the-challenge-of-legacy-systems/ or visit GoRedux.AI to learn more.
Meet Luca Moukheiber. A rising college sophomore, he is a member of the 2023 Karsun Innovation Center Internship Program. He worked alongside artificial intelligence (AI), federal acquisitions and data solutions experts as part of a project team developing a federal contracts management proof of concept. In the interview below, we learn more about Luca, his project using a Large Language Model to generate code and his favorite parts about working with our Innovation Center.
First please tell us about yourself. Where are you going to school? What are you studying? What do you like to do in your free time?
I am an Echols Scholar about to start my second year at the University of Virginia, where I am majoring in computer science. I enjoy hiking, biking, paddle boarding, and playing the guitar in my free time.
Could you share a little bit about the project you worked on as part of this internship? What challenge does it solve? What technologies and tools are you using?
As part of the Karsun initiative to explore the integration of generative AI into application development, I developed a file attachment feature used in a proof of concept application using Large Language Model (LLM) technology to generate code for certain parts of my project. I created a custom interface for users to upload, view, or delete documents as part of a reporting system. My project solves the challenge of improving efficiencies and reducing costs associated with federal contract management. This task involved working on both the front and back end to store documents in a database and the cloud. Leveraging AI to reduce manual code writing reduces development time and improves efficiency. The technologies that I used in this project were GPT-4, Angular, Spring Boot, Postgres, AWS S3, LocalStack, Jest, Nx, Flyway, and Podman.
What is your favorite part about working with the Karsun Innovation Center? Is there a weekly meeting or ritual you enjoy? The opportunity to learn more or get a new certification?
My favorite part of working in the Innovation Center is having the opportunity to develop cutting-edge solutions to novel problems. The projects evolve rapidly, with ample space for creative thinking and problem-solving. I appreciate Karsun’s emphasis on intern learning. I am currently studying to become certified as an AWS Developer Associate.
What is the biggest takeaway from your experience as an intern at Karsun?
My biggest takeaway is that keeping an open mind, being adaptable, and continuously learning are core software development skills. I came in with no Angular experience, and understanding how everything worked together in the codebase was difficult at first. However, by taking courses, I saw how the material I learned applied to the real project I was working on, enabling me to build my own feature. There were also situations where I had to change my approach because I ran into blockers, which took me extra time to figure out but strengthened my problem-solving abilities.
Luca’s internship was supported by the Karsun Solutions Innovation Center Practice Areas. Learn more about Karsun’s Acquisitions Management Modernization solutions. Connect with Luca on LinkedIn.
Every summer Karsun embeds interns in our Innovation Center to work alongside our technology experts, prototyping solutions to support our customers. 2022 Intern Akhilesh Varanasi used synthetic data to address a common privacy concern, personally identifiable information (PII.) Using synthetic data, an artificial set of data is created to perform ML/AI work preventing exposure of sensitive PII. In the interview below, Akhilesh describes his experience in the Karsun Innovation Center and his synthetic data internship project.
First, please tell us about yourself. Where are you going to school? What are you studying? What do you like to do in your free time?
Hi all! My name is Akhilesh Varanasi. I’m currently a rising junior at the University of Washington in Seattle, where I’m a double major in Computer Science and Astronomy. In my free time, I like reading and playing basketball.
Could you share a little bit about the project you worked on as part of this internship? What challenges does it solve? What technologies and tools are you using?
For most of my internship, I worked on the Synthetic Data project. The purpose of this project was to create PII anonymized ‘fake’ data for Machine Learning/Artificial Intelligence use cases. I mostly worked with Python, the Synthetic Data Vault libraries, and graphing frameworks like matplotlib. My main tasks were to create accurate Synthetic Data models and to find generic ways to graphically represent all forms of tabular data. I also worked with AWS Lambda and the AWS CLI to run tests.
What is your favorite part about working with the Karsun Innovation Center? Is there a weekly meeting or ritual you enjoy? The opportunity to learn more or get a new certification?
My favorite parts of working at the Karsun Innovation Center were the input I had in the development process and the team I worked with. I always felt like my opinion was respected at meetings, even in a room full of people that were far more experienced than me. I also had a great time working with the team, everyone was so willing to help each other and it felt like a comfortable, collaborative environment.
What is the biggest takeaway from your experience as an intern at Karsun?
My biggest takeaway from my experience at Karsun is that taking initiative is important. To be a valuable part of a team I have to research topics by myself and come up with goals to structure my approach to a problem.
Akhilesh was mentored by Srikanth Devarajan, Director, Karsun Innovation Center Data Practice.
Every summer Karsun embeds interns in our Innovation Center to work alongside our technology experts, prototyping solutions to support our customers. 2022 Intern Akhilesh Varanasi used synthetic data to address a common privacy concern, personally identifiable information (PII.) Using synthetic data, an artificial set of data is created to perform ML/AI work preventing exposure of sensitive PII. In the interview below, Akhilesh describes his experience in the Karsun Innovation Center and his synthetic data internship project.
First, please tell us about yourself. Where are you going to school? What are you studying? What do you like to do in your free time?
Hi all! My name is Akhilesh Varanasi. I’m currently a rising junior at the University of Washington in Seattle, where I’m a double major in Computer Science and Astronomy. In my free time, I like reading and playing basketball.
Could you share a little bit about the project you worked on as part of this internship? What challenges does it solve? What technologies and tools are you using?
For most of my internship, I worked on the Synthetic Data project. The purpose of this project was to create PII anonymized ‘fake’ data for Machine Learning/Artificial Intelligence use cases. I mostly worked with Python, the Synthetic Data Vault libraries, and graphing frameworks like matplotlib. My main tasks were to create accurate Synthetic Data models and to find generic ways to graphically represent all forms of tabular data. I also worked with AWS Lambda and the AWS CLI to run tests.
What is your favorite part about working with the Karsun Innovation Center? Is there a weekly meeting or ritual you enjoy? The opportunity to learn more or get a new certification?
My favorite parts of working at the Karsun Innovation Center were the input I had in the development process and the team I worked with. I always felt like my opinion was respected at meetings, even in a room full of people that were far more experienced than me. I also had a great time working with the team, everyone was so willing to help each other and it felt like a comfortable, collaborative environment.
What is the biggest takeaway from your experience as an intern at Karsun?
My biggest takeaway from my experience at Karsun is that taking initiative is important. To be a valuable part of a team I have to research topics by myself and come up with goals to structure my approach to a problem.
Akhilesh was mentored by Srikanth Devarajan, Director, Karsun Innovation Center Data Practice.