As agencies such as the Internal Revenue Service shrink workforces and adopt leaner operational models, resources to support large scale modernization efforts are increasingly constrained. It is under this strain that John Gilroy opens a recent episode of the Federal Tech Podcast recorded live at the AWS Summit in Washington, D.C. Karsun Co-Founder Kartik Mecheri joins John and former General Services Federal Acquisition Services (GSA FAS) Commissioner Alan Thomas for a discussion on AI, digital workforces and the future of government modernization.

As John observes, the landscape of federal technology is at a critical juncture. Imagine systems born in the 1960s, like COBOL, still running essential government operations, while the average federal worker was born almost two decades later! This generational gap, combined with a shrinking government workforce creates an undeniable need for modernization.

At the same time, government agencies face immense pressure to deliver better experiences for their customers while grappling with complex legacy systems and processes that have been perfected over decades. These systems, often mainframes, are not just old; they are mission-critical, meaning they cannot be simply turned off for upgrades. Modernizing them is, as John notes, akin to “doing a little upgrade while you’re flying the plane”.

The AI Imperative: Introducing ReDuX AI-Powered Modernization

Enter Artificial Intelligence, AI. Government agencies are increasingly interested in AI for modernization to pick up the slack from fewer personnel and improve service delivery. Karsun Solutions offers a powerful tool designed specifically for this challenge: ReDuX.

The ReDuX Modernization Platform Addresses Several Key Pain Points:

Declining Subject Matter Expertise: As veteran employees retire, the deep knowledge of these legacy systems often walks out the door with them. Redux.ai aims to capture this expertise.
Complex Migrations: Converting decades of intricate code and interactions into modern architectures within a tight timeframe (e.g., 40 years of work into a 5-year project) is a monumental task.

How ReDuX Transforms Modernization

Redux uses specialized AI agents to streamline the modernization process:

Blueprinting Agents: These agents delve into legacy code, extract crucial information, and integrate it with user guides and demonstrations. The goal is for the agents to become the subject matter expert on the legacy system.
Modernization Agents: Once the legacy system is understood, these agents can convert the code to run on modern cloud platforms like AWS or Azure. They ensure the new system adheres to the required architecture and security posture of the agency.

Karsun has successfully used ReDuX to migrate multiple mainframe COBOL applications and other legacy systems (like Visual Basic 6, VB6) to modern technologies. This approach can accelerate modernization by 4x and reduce costs by 2x, reducing key modernization tasks by months and even years.

The Rise of the Digital Workforce

A key concept driving this transformation is the “digital workforce”. This involves building digital equivalents or “digital assistants” for every role in the software development cycle. Imagine:

An architect agent that understands your target architecture and generates diagrams, documentation, and security architecture.
Agents for creating unit tests, generating code, or ensuring security compliance.
Agents for business analysts to create user stories.

The idea is to empower agile teams with digital support allowing them to focus on strategic, high-value, creative, and innovative work. While managing human teams is a well-understood skill, managing these “agents” is a new frontier that the future leaders will need to master.

Looking ahead, experts predict that within a year, we will see more demonstrable examples of AI deployment with clear business benefits. Leaders will need to balance AI’s promise with risks. As they conclude their discussion, John, Kartik and Alan discuss strategies for mitigating AI hallucinations, improving accuracy and reducing security risks. They also discuss identifying technology partners with the strategic relationships required to effectively implement technology in the evolving environment.
For federal legacy systems the modernization journey is complex, but with innovations like Karsun Solutions and the ReDuX team, the path to a more efficient, agile, and secure government future is becoming clearer.

Tune in to the podcast to learn more or check out GoReDuX.ai

At Karsun Solutions, we’re constantly pushing the boundaries of innovation, especially when it comes to modernizing legacy systems. Our monthly Innovation Town Halls showcase how our experts use emerging technologies like automation and AI to solve real-world customer challenges. Recently, we had two insightful presentations that highlighted the power and versatility of our ReDuX AI-powered modernization platform in transforming complex legacy code using an AI code parser. That team recently summarized their findings on our GoReDuX Blog. Today we’re sharing their insights below.

Natural/ADABAS Modernization with ReDuX AI Code Parser

A common pain point for mainframe customers involves systems written in legacy Natural code with ADABAS. The desire to move away from these systems is driven by several factors, including proprietary software costs, workforce shortages and the fine-tuning required for proper system performance.

While other modernization tools offer automations for refactoring or replatforming, they often fall short in providing deeper insights. Moreover, they do not lay the groundwork for future enhancements.

The ReDuX Solution

Karsun expert Eamon Cusic shared how his team addressed this. Using ReDuX, they developed a Natural parser capable of assessing both the syntax and semantic structure of the code The team utilized ReDuX Blueprinting agents to analyze user behavior, software module code, and VSAM database schema.

This enabled them to provide context within the VSAM, including crucial elements like core business logic, data flow, and screen flows. With ReDuX Blueprint citations, Eamon’s team could even examine exact window management subroutines, providing unprecedented clarity.

Conquering VB6 and Unsupported Third-Party Components

Raminder Saluja, an AI for modernization leader in our aviation practice, shared another critical challenge facing his customer. A vital legacy application faced obsolescence because its language and third-party components were no longer supported, making modifications and bug fixes nearly impossible. The looming threat? The application was anticipated to stop working with the next Windows update.

The ReDuX Solution

Raminder’s team needed a tool for rapid modernization. ReDuX proved to be the solution, not only capable of parsing VB6 code but also validating requirements and generating test cases as part of the modernization process. After leveraging the Blueprinting agents (like those used for Natural), Raminder’s team extended ReDuX’s VB6 parsing to its code companion code generation agent. The ultimate goal: migrate VB6 to a VB .Net application.

This approach dramatically reduced the modernization timeline. While traditional methods can take over a year, this ReDuX-powered effort is expected to be completed within a 6-month timeframe.

ReDuX: A Mature Framework for Any Legacy Language

What these case studies demonstrate is ReDuX’s incredible adaptability. Whether you’re dealing with Natural, VB6, Oracle Forms/Apex, or other legacy coding languages like COBOL, ReDuX provides a mature framework that allows for the addition of new parsers and libraries. Depending on the language’s complexity, a ReDuX AI engineering team can typically write new parsers in just 2-6 weeks.

Both Eamon and Raminder leveraged this mature process to tackle previously intractable code parsing problems, transforming challenging modernization efforts into achievable projects.

ReDuX empowers Architects, BAs, Product Owners, Designers, Developers, and Testers to achieve significant improvements. Connect with us to discover how ReDuX can tackle your legacy code challenges and accelerate your modernization journey!

Lisa Hoover, Head of Experience and Design at Karsun Solutions recently joined John Gilroy and the Federal Tech Podcast. In this insightful discussion, they delve into the evolving Customer Experience (CX) landscape in the midst of rapid technological change.

Shifting from UX to CX

In their discussion, Lisa describes the evolution of focus from user experience (UX), which centers on digital product solutions, to CX, an all-encompassing approach to technology products. CX considers entire interactions a person has with an organization’s brand, throughout their entire relationship with that brand including solutions, services, and of course, the UX on an organization’s website.

In the federal sector, there’s a growing awareness of CX. This was driven by previous executive orders on federal customer experience and service delivery. However, Lisa notes that initially, the focus was often on meeting requirements, simply “checking a box” for CX rather than truly embracing human-centered design principles.

The Legacy System Challenge

A significant hurdle in improving federal CX is the prevalence of legacy IT systems. These monolithic systems with complex, entangled codebases make modernization difficult. Customers often get stuck with inefficient processes due to these outdated applications, and manual patches only exacerbate the problem. Lisa observes this is why a “checking-the-box” approach to requirements is not enough, organizations need to implement a holistic, product mindset.

Unlike commercial companies that can independently implement user-friendly changes, the federal government faces limitations due to these legacy systems and strict compliance requirements, including those surrounding data privacy and security. That’s why, Lisa notes, only 23% of Americans believe federal services are easy to navigate, indicating a significant need for improvement

Measuring CX Effectiveness

Measuring the impact of CX improvements is more complex than measuring UX, where metrics like bounce rate and time to task completion are readily available from web analytics and other resources. In the past, insights into customer challenges were often buried in support tickets, making it difficult to establish a baseline for improvement. However, with the rise of artificial intelligence (AI), organizations can tease apart the complex relationships between online and offline activities, paint a clearer picture, and improve customer experience.

The Dawn of Approachable AI

Shifting the conversation to the role of AI in addressing these challenges, Lisa emphasizes that AI has become increasingly “approachable.” Modern AI has moved from an abstract concept to a mainstream technology, largely due to advancements like OpenAI. This increased familiarity makes federal customers more open to accepting AI-powered solutions.

AI for Efficiency at Scale

AI presents a remarkable opportunity to achieve efficiency at scale within federal agencies. Instead of replacing humans, AI can help individuals become more efficient by automating manual tasks and allowing them to focus on higher-value work. For instance, developers currently spend a significant amount of time troubleshooting legacy systems; AI can help reduce this well-known “time suck.”

A Blueprint for Modernization

Karsun Solutions offers a potential solution with its ReDuX AI-powered modernization platform. ReDuX creates a blueprint of a legacy system, breaking down the architecture and the behavior of the system’s users. This provides situational awareness and context awareness, allowing various stakeholders to understand the system as a whole. This comprehensive view helps teams devise strategic modernization plans beyond simply “patching holes.” By offering this overarching blueprint, ReDux aims to take the guesswork out of legacy system challenges.

Streamlining Decision-Making with AI

AI, when integrated with platforms like ReDuX, can significantly streamline decision-making and accelerate modernization efforts. By providing a holistic view of complex systems, teams can identify areas for improvement, implement standardized solutions, and measure the impact. AI-powered tools like chatbots and augmented reality can further guide users and help interpret data for UI improvements at scale.

The Future of Efficiency and Enhanced CX

Lisa concludes by expressing excitement about the future. She envisions increased adaptation of AI-enhanced solutions like ReDuX to modernize legacy systems more efficiently. The goal is to create federal services that are more usable, faster, and ultimately lead to satisfied and joyful customers. The key takeaway is that efficiency, enabled by understanding the big picture and leveraging AI responsibly, will be crucial in transforming federal IT and customer experience.

To learn more about Karsun’s ReDuX modernization platform, visit GoReDuX.AI. To listen to the full podcast, tune in at https://www.theoakmontgroupllc.com/ep-220-how-customer-experience-can-make-or-break-federal-technology-initiatives/

Government agencies facing an increasing mandate to move from legacy mainframe systems. The solution, generative AI. Now, agencies no longer need to fear the tradeoff between migration risk and the opportunity available in the cloud. In this case study featured on the AWS Public Sector Blog, our Karsun experts share their experience accelerating modernization with AI.

This case study features Karsun Solutions’ ReDuX AI powered migration and modernization platform. It offers a compelling approach for enterprises considering mainframe migration. Sharing their experience modernizing legacy applications for one of our government customers, this case study demonstrates what happens when modern AI tools meet modern software development practices.

Deep Insights Using Amazon Bedrock

ReDuX is designed to tackle typical obstacles in mainframe modernization, such as undocumented business rules, technical complexities, and regulatory compliance. Its approach is inspired by Karsun’s decade and a half modernizing complex enterprise systems for the federal government. ReDuX utilizes generative artificial intelligence (GenAI) powered by Amazon Bedrock to analyze and understand legacy systems.

Using Bedrock the Karsun team accessed high-performing foundation models from leading AI companies via a single API. Building their ReDuX platform on top of the resources provided by Bedrock, our team created an AI powered toolkit for identifying and mapping the complex business rules and processes embedded within mainframe applications. This facilitates a smoother transition to modern architectures. Further, by providing a structured approach, ReDuX reduces risks associated with legacy system modernization.

Matching AI with Modern Microservices Architecture

In the case study, we share how using our AI powered platform, we enabled our government customer to migrate from monolithic mainframe systems to microservices-based architectures on AWS. This shift enhances scalability, flexibility, and maintainability of applications, aligning with modern IT strategies.

It also allowed our team to focus on security and privacy. Recognizing the importance of enterprise-grade security and privacy, especially in government and regulated industries, the platform incorporates robust measures to protect sensitive data during and after the migration process.

Furthermore, migration to the cloud enables secure-by-design architecture. Using AI powered tools, like those available on the ReDuX AI platform, lets our agency customers access the benefits of the cloud while reducing migration risks. Written in a modern language, it alleviates workforce concerns and eliminates long-term maintenance issues arising from the aging, dwindling population familiar with COBOL and other outdated languages.

By demonstrating a successful implementation of generative advanced AI technologies and cloud services to migrate and modernize legacy systems, this case study from our team offers valuable insights. It presents a potential roadmap for organizations seeking to undertake similar modernization initiatives. Head over to the AWS Public Sector blog for deeper insights on AI-driven modernization and a technical breakdown of our solution.

We recently announced that we were appraised at CMMI Level 5 DEV for a third time. This maturity appraisal comes from ISACA, a global professional association focused on governance of enterprise IT, and represents the highest maturity level in that organization’s CMMI (Capability Maturity Model Integration) framework.

Few companies meet the requirements for CMMI Level 5 Dev and we’re honored to appraise at this level three times. We’re proud to deliver quality consistently at the highest levels. Artificial intelligence, AI, powers the statistical and quantitative techniques used to meet our performance objectives.

In fact, in 2024 experts from our Karsun Innovation Center spoke at the ISACA CMMI Conference. At this conference, they presented a case study from one of our teams supporting a government agency customer. This team used AI tools included in our ReDuX AI platform to enhance efficiency while creating production ready code at a rate faster than if human teams produced that code on their own.

To better understand how AI can drive these process improvements, we share some insights from their talk below. For deeper insights on AI, development and modernization, Discover How ReDuX AI Works.

The Case for AI Powered Process Improvement

We presented this real-world case study at the annual CMMI conference in Phoenix, Arizona in 2024. CMMI appraisals were originally designed to help the Department of Defense understand its process. Today organizations around the world now seek out CMMI assessments. Karsun’s software development methodology is appraised at the highest tier for software development appraisals indicating we use a data driven process to analyze, assess and continually improve our practices.

The story begins in the Karsun Innovation Center. This center houses the Karsun research and development unit responsible for prototyping and integrating emerging technology and connecting our team members with industry technology leaders and experts. Part of the work of the Innovation Center includes building toolkits, playbooks and other resources.

That includes an agile platform we built called GoLean that’s used by our software development teams. Using this platform, we tracked performance data, made adjustments, and observed the impact of our process improvements using dashboards and other tools to gain insights. Using the tools in this platform our teams compared incremental improvement to past performances, identified practices that were outliers from our average performance, and made adjustments to reduce the impact and risk of those outlier events. This approach to agile development resulted in our first two CMMI Level 5 DEV appraisals.

Meanwhile, artificial intelligence opened up the door to truly optimize our practice. We began building AI tools that could handle very high dimensionality. In other words, the model used by the AI needed to handle data with many related factors.

This allowed us to understand the relationship between processes and the impact of changes to those processes. We could now better assess moving certain processes to the left, testing new automation practices or adding new DevOps or CI/CD tools. We could now measure holistic improvement to more rapidly scale and drive improvements among our development teams enhancing our overall efficiency.

The Results: Elevating Efficiency with AI

This, when combined with other tools in our AI platform, boosted our team’s efficiency as they modernized a 30 year old mainframe system. With the use of AI, our team saw a 22.5% increase in productivity! What’s more, using AI, they developed reusable resources to further optimize our processes.

In addition to new and improved methods for measuring process improvement, our ability to deliver high quality code quickly was further improved by AI agents. From code generation to scalability templates, agentic AI introduced yet another opportunity to further enhance our efficiency. To uncover this part of our toolkit visit us at GoReDuX.AI.

Agile development is in our DNA. Now using AI to boost efficiency in government, we’re leading the pack with high quality software and modern enterprise systems to meet agency missions.

Ready to partner with proven performers? Contact our team here to get started!

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!

Happy Valentine’s Day from the Enterprise Modernization Experts! Today, we’re sending our love to the designers, developers, and data engineers who deliver excellence to our government customers and the American people. Driving this performance are the dedicated teams diving into the latest technology solutions. Among those cutting edge solutions are these digital transformation trends we love here at Karsun Solutions.

Designing with a Product Mindset

The Product Mindset empowers teams as they design applications in a way that adapts to the ever-changing digital landscape. As we enter a period requiring adaptability and a forward-thinking approach, the Product Mindset asks teams to consider how the system will be used now and in the future and how they can introduce efficiency now while building to scale.

This mindset emphasizes moving from a “building” to a “dwelling” perspective. This focuses the process on continuous design as a form of continuous improvement. That includes modeling user experiences, using modern platforms, and implementing layered designs. Learn how Karsun does this with our Digital Transformation Toolkit in this white paper from the Karsun Innovation Center.

https://karsun-llc.com/resource/design-for-every-next-2/

Generative AI for Human-Centered Design

Another key digital transformation component is human-centered design (HCD.) This approach centers design using practices that identify whether the product matches the expectations of its human users. This is achieved by building in continuous feedback and using practices that assist product teams as they identify whether design supports or hinders users.

While human-centered design brings humanity back to software development, it also helps teams ensure the product is used as intended. It uses tools, like those built with machine learning (ML) and artificial intelligence (AI), to process user data and generate new insights. From these behavioral insights business analysts and others can more quickly generate requirements to ensure functionality carries over to the new systems built by the product team.

As a final process improvement and efficiency-boosting feature, systems using Generative AI learn from the best practices of the development teams using these tools. When well integrated into platforms like Karsun’s ReDuX AI, the team may use AI to identify the practices that best help achieve their product goals. Based on these insights, the team can add guard rails, further engineer their model, or use agentic AI to generate code, templates, and other resources in line with those recommendations.

Zero Trust Architecture Boosted by Security-Led Practices

When using zero trust architecture (ZTA), systems continuously validate every interaction with the system. Using this approach, teams build systems that limit the ability of people and devices to access it, assuming that by default, they are not to be trusted. Zero trust best practices are essential when building secure architecture designed to adapt to changing needs and evolving threats. The ZTA approach includes well-architected practices. It also includes integrating emerging technologies.

When teams use security-led practices, such as zero trust architecture and well-architected principles, they can now use AI to enhance their capabilities. That includes using predictive AI to identify risks and generative AI (GenAI) to address those hazards. Teams using our ReDuX AI-powered digital transformation engine use GenAI to proactively recommend best practices, generate guard rails based on established policies, and build templates so they can scale their practices more effectively.

At Karsun, we design large-scale government IT solutions that enhance the capabilities of our agency partners and drive performance. Our commitment to solid digital transformation and design practices is part of our enduring commitment to technology solutions for every next. Our experts deliver these robust enterprise solutions at agencies across the federal government. At the same time, our innovators explore, prototype, and implement the latest technologies as part of delivering truly transformative solutions. If any of these trends pique your interest, we invite you to connect with our Karsun Innovation Center team and discover how you can begin your technology journey.

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.

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.