Every program office running a legacy system is on a clock it did not set. The people who know why the code does what it does are retiring, and most of what they know was never written down or if it was, is now out of date. The rules are still there, encoded in the system itself. What is disappearing is the ability to read them.

The Software Acquisition Pathway (SWP) asks teams to value working software over comprehensive documentation. Yet, documentation is what survives to accelerate the work of future teams, and it is the first thing deferred when delivery is the measure. A program can  deliver on cadence for years, and still arrive at a system that no one remaining can explain, secure, or re-compete.

The question is not whether to document. It is whether understanding a system still has to cost what it used to.

What the SWP Requires

Under DoD Instruction 5000.87, the pathway establishes the artifacts a program produces to move from one iteration to the next. Those artifacts are what let subsequent teams secure, maintain, and enhance the software after the current team is gone.   

Rather than collecting the artifacts from the people who remember the system, teams can now derive them from the system itself. Karsun’s ReDuX analyzes the codebase and generates the underlying material for these documents with citations back to the specific code that governs each one. The citation is the part that matters. It means an assertion about the system can be checked against the system, by anyone. 

Dynamically Generate Requirements 

One of the first steps in the pathway is capturing the overarching requirements that feed a Capability Needs Statement (CNS) or User Agreement (UA) or other similar document.  As ReDuX analyzes user demos and the codebase, it produces requirements and user flows, each citing the specific legacy code that governs it. The requirements are written as behavior-driven given-when-then (GWTs) statements, a form that is testable by agents and reviewable by the developers and subject matter experts who validate them. Because each statement traces to the source code that produced it, any reviewer can confirm it, not only the teams that were there when the system was built.

Architecture Documents

A Software Acquisition Strategy (SAS) requires documentation of both the legacy architecture and the target. The legacy half is where programs get stuck. The available diagrams were drawn years ago and have drifted from what is actually running, and the people who could correct them are the same people who are leaving. ReDuX Blueprinting Lenses derive the legacy picture from the application’s own code and artifacts, covering data and job flows, schemas, endpoints, and screen flows. Because that picture comes from the system rather than from memory, the strategy rests on what the system does today. It is also the precondition for a modular open systems approach (MOSA). Decomposing a system into modules with defined interfaces requires knowing where the seams actually are, and on a legacy system nobody knows that until it is derived. 

Scoping, Estimating and Forecasting Work

The same blueprint also changes what a program can see when it plans. Estimating work on a legacy system usually means estimating against an incomplete picture, and the gap shows up later as cost and/or schedule overruns. Working from a dependency map derived from the application itself, teams can find duplicate functionality, sequence enhancements against what actually depends on what, pay down technical debt deliberately rather than opportunistically, and remove dead code with the evidence to prove it is dead. Committing to an annual capability delivery cadence is easier when the commitment rests on the system as it is.

The pathway asks programs to move fast. The clock asks them to move fast without losing what they know. Those pull against each other only if understanding a system still has to come from the people who built it.

Everything described here belongs to the government. The requirements, the architecture, the constraints, and the traceability are platform-neutral and readable without Karsun tooling, which means a program office can hand them to any team, on any target, including a competitor. That is the point. The documentation the pathway asks for should outlast the vendor that helped produce it, and it is worth capturing now, while the people who best understand their legacy systems are still here to ask.

Every year Karsun welcomes interns to our offices to collaborate, innovate and build alongside our team members. This year some of our Summer Interns supported corporate and operational teams. One of these was Daksh Badri, a rising sophomore at Columbia University majoring in Economics-Political Science and Medical Humanities. 

Daksh served as a Legal Intern in Karsun’s Contracts Department and his mentor Jennifer Cummings, Senior Director. In this role, he developed a comprehensive understanding of the legal framework which Karsun operates as a federal contractor and commercial partner. That work served as a foundation for his development of his Intern Project provided by his mentor the Karsun AI Contract Reviewer (KAICR). This innovative AI program independently analyzes and redlines responses to assist contract personnel. Notably, his work represents one of the first concrete deployments of an AI agent within Karsun’s corporate departments. As a result, his work was featured in our September Innovation Town Hall.

After earning his Bachelor’s degree, Daksh plans to attend law school, focused on the intersection of law and ethics in the coming age of AI automation to help organizations navigate complex legal accountability and ethical challenges while leveraging emerging technologies to improve efficiency, accessibility, and decision-making.

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?

During my time at Karsun, I had the opportunity to work under the mentorship of Jennifer Cummings, Senior Director of the Contracts department, whose leadership spans Federal Procurement, Contract Law, Contract Development, and Business Development. This experience provided me with first-hand exposure to the legal and operational complexities of a growing technology company.

Building on that foundation, I designed and developed KAICR. This AI-powered review agent is designed to analyze Non-Disclosure Agreements, identify legal risks, and recommend revisions to contractual clauses based on a tiered framework aligned with Karsun’s business objectives and values provided by my Mentor and former NDA revisions. By streamlining the initial contract review process, the tool helps improve consistency, efficiency, and decision-making while supporting the legal team’s review of NDAs. Karsun plans to leverage KAICR as part of its NDA review process and is exploring opportunities to expand its use to additional contract types, such as teaming and subcontractor agreements. Contributing to a solution with the potential to enhance Karsun’s legal operations has been an incredibly rewarding experience and sparked my interest in the intersection of law, AI, and business strategy.

What was your favorite part about interning at Karsun’s Contracts Department?

My favorite part of interning at Karsun was the opportunity to continuously experiment, learn, and grow under the mentorship and guidance of the company’s open and collaborative culture. My project in nature allowed me to collaborate with departments outside of just Contracts, and it helped me to feel comfortable during my first few weeks, as I was encouraged to ask questions while also being given the independence and creative freedom to explore all possible options. Karsun’s collaborative culture allowed me to better understand the requirements of the Contracts department, its obligations to the company and risk mitigation as well as steps to take to develop a meaningful and efficient product that addresses those needs.

What is your biggest takeaway from your experience as an intern at Karsun?

The biggest takeaway from my experience at Karsun was gaining practical, hands-on exposure to the intersection of law and AI, which is such a unique domain: we all know that AI will be incorporated into the legal field, yet there haven’t been widespread steps by lawyers and companies to understand, regulate, and train AI to best suit legal needs. Jennifer provided invaluable mentorship and guidance, while the Karsun Innovation Center (KIC) team provided me with the resources and knowledge necessary to develop KAICR.

I am deeply grateful to Karsun’s Co-Founders Sundar Vaidyanathan and Kartik Mecheri for the opportunity to work at Karsun and to contribute to such a dynamic company that has strengthened my passion for combining legal expertise, emerging technologies, and business innovation. These experiences not only enhanced my professional skills but also made my internship a truly rewarding and memorable experience.

Karsun Solutions is growing and hiring! That includes one of our hottest jobs: Lead Solution Architect. Working out of our Herndon, Virginia headquarters this technology expert has a deep understanding of application modernization, cloud-native architecture, and modern software development practices to drive the transformation of legacy applications using traditional architecture combined with low code application platforms (LCAP) and AI/ML technologies. Join us as we spotlight this critical enterprise modernization role and share a day in the life of a Lead Solution Architect.

A Day in the Life of a Lead Solution Architect at Karsun Solutions

• Directing Cloud-Native Modernization & Microservices: Setting technical direction to transform legacy monolithic government systems into scalable, cloud-native microservices using AWS, Azure, or GCP, serverless patterns, and containerized platforms like Kubernetes.
• Building Proofs of Concept with AI, ML, & Low-Code: Getting hands-on in Python to prototype machine learning pipelines, evaluate Generative AI tools (like GitHub Copilot), or implement low-code workflows via Power Automate and UIPath to accelerate rapid application development.
• Enforcing Architecture Governance & DevSecOps: Facilitating architecture reviews, leading technical spikes, and creating Architecture Decision Records (ADRs) while collaborating with SRE and security teams to enforce zero-trust security and federal standards like FISMA, FedRAMP, and NIST.
• Aligning Federal Leadership & Stakeholders: Translating complex technical roadmaps into executive narratives and presenting modernization strategies to federal agency acquisition leaders and IT executives to gain program buy-in.
• Hands-on Mentorship & Code Reviews: Conducting live technical demonstrations, reviewing production pull requests in languages like Java, Python, or TypeScript, and mentoring senior engineering staff on modern practices.

Frequently Asked Questions (FAQs)

Modernizing legacy applications has become a strategic priority for organizations preparing for AI-driven innovation. However, many organizations hesitate when figuring out how to begin before committing significant resources to changing decades-old systems they may not fully understand.

This is where the AWS Migration Acceleration Program (MAP) can help. MAP reduces both financial and technical barriers. When working with a Migration and Modernization Competency Partner, it provides funding and guidance to assess, mobilize and modernize with greater confidence. And, for organizations considering a ReDuX pilot, MAP provides a way to get started with a focused assessment before committing to a larger modernization effort.

What is AWS MAP?

AWS MAP is a comprehensive cloud migration program that combines proven methodologies, technical guidance, AWS expertise, and funding support to help organizations accelerate modernization initiatives. Rather than expecting organizations to move directly into implementation, MAP follows a phased approach that helps teams understand their environment, build a migration strategy, and execute modernization with reduced risk.

The program is structured around three phases:

• Assess – Evaluate existing applications, understand dependencies, identify business value, and determine the best modernization approach.
• Mobilize – Build the migration foundation, establish processes, prepare teams, and validate the modernization strategy.
• Migrate & Modernize – Execute migration activities and modernize applications using AWS services and best practices.

For many organizations, the most valuable part of MAP is that funding is available even during the early assessment stage, before major modernization work begins. MAP funding is available through AWS Partners, including Karsun, that have achieved the AWS Migration and Modernization Competency. 

Why the Assessment Phase Matters

One of the biggest obstacles to modernization is uncertainty. Legacy applications often contain decades of undocumented business logic and institutional knowledge that exists primarily within the code itself. Organizations are understandably reluctant to invest in a large modernization effort without first understanding what they are working with. MAP helps remove that uncertainty.

Through assessment funding, organizations can gain visibility into their applications before making larger investment decisions. Instead of relying on assumptions, teams can evaluate complexity, identify risks, and build a roadmap based on real insights.

This allows decision-makers to answer critical questions such as:

• What business rules exist inside the application?
• Which systems are tightly coupled?
• What should be modernized, retained, consolidated, or retired?
• What level of effort should be expected?

Having these answers upfront leads to better planning and significantly reduces modernization risk.

Lowering the Barrier to Getting Started

Since MAP provides funding during the assessment phase, organizations do not have to begin with a large modernization commitment. Instead, they can start with a focused engagement that helps them understand their environment and determine the right path forward.

This approach is especially valuable for organizations considering large-scale legacy transformation. Rather than committing to a full migration immediately, they can validate assumptions, reduce uncertainty, and build executive confidence before moving into implementation. 

How Karsun Helps Organizations Maximize MAP

Karsun helps organizations take full advantage of MAP while accelerating modernization with AI-powered insights. 

Our AI-powered ReDuX platform naturally aligns with the MAP framework. During the Assess phase, ReDuX creates a comprehensive blueprint of legacy systems by analyzing source code, business logic, application dependencies, APIs, and data relationships. Instead of relying on assumptions, organizations gain a living understanding of how their applications actually operate. This foundation allows teams to make informed modernization decisions before writing new code or beginning migration efforts.

From there, ReDuX supports modernization throughout the remaining MAP journey by helping teams:

• Discover and document legacy systems
• Preserve critical business logic
• Accelerate modernization with AI-assisted workflows
• Reduce delivery risk through human-in-the-loop governance

The result is a modernization process that is both more informed and more predictable.

Start with Knowledge, Not Guesswork

Modernization does not have to begin with a leap of faith. With AWS MAP funding, organizations can start by understanding their legacy applications, identifying modernization opportunities, and building a roadmap based on evidence rather than assumptions. By combining AWS’s proven migration framework with Karsun’s AI-powered modernization capabilities, organizations can reduce risk, accelerate decision-making, and move toward modernization with greater confidence. Sometimes the most important step is not migration itself but rather, gaining the clarity to know what comes next.

When COVID 19 hit, state Unemployment Insurance (UI) systems faced an unprecedented demand spike and aggressive fraud rings. Most systems survived, but few held up well. Today, many still run exactly as they did and that is the core problem.

Stable Isn’t the Same as Ready

Surviving a crisis is not the same as being built for one. Fixed legacy infrastructure cannot expand on demand. The next downturn, policy change, or fraud wave will test these systems again.

This reality has shifted federal priorities. Early American Rescue Plan Act funding focused on immediate emergency scaling. Current federal support emphasizes proactive fraud prevention and modular defenses. While original allocations were reduced under the Fiscal Responsibility Act of 2023, funding remains available including 600 million dollars from the Department of Labor dedicated to helping state agencies implement modular architectures. However, this funding window will not stay open forever. States can no longer afford high risk, multiyear overhauls. They must maximize federal dollars through targeted modernizations.

Architecture Built for a Different Era

System instability stems from two structural flaws:

• Batch Oriented Processing: Legacy cores rely on overnight and periodic batch cycles instead of real time processing. When volume spikes, batch windows back up and stall the entire system.
• Fragmented Fraud Detection: Fraud tools are bolted onto the core rather than integrated into it. They run on delayed data exactly when organized fraud networks strike fastest.

Agencies often stall due to rigid budget cycles or resort to standalone fraud tools that treat symptoms rather than the underlying system.

How ReDuX Modernizes UI Systems Without the Risk

Fixing monolithic systems requires breaking them down into microservices, which are smaller, independent modules that update and scale without disrupting the entire application.

Traditional tech partners attempt this by deploying massive teams to manually map systems and draft multiyear roadmaps. This approach is slow, costly, and high risk. Modernization does not require a rip and replace gamble.

Karsun’s ReDuX platform uses agentic AI to modernize legacy cores incrementally, avoiding the outage risk that stalls modernization efforts:

• Strategic Architecture and Workflow Optimization: System experts collaborate with intelligent tools to analyze legacy dependencies, refine workflows, and architect a scalable target environment. 
• Risk Mapping: Blueprinting agents map legacy code and its connections to fraud tools, highlighting hidden dependencies before execution. 
• Real Time Transition: Agents replace overnight batch cycles with real time streaming pipelines, integrating fraud detection directly into claims processing so threats are caught while actionable. 
• Human Oversight: Domain experts review and guide every agent task, ensuring continuous accuracy while compound skill improvements enhance efficiency over time. 
• Parallel Migration: Legacy and modern systems run simultaneously. Agencies migrate workflows in validated phases, maintaining service continuity without betting everything on a single cutover date.

The Bottom Line

Agencies that wait for the next crisis end up repeating the same frantic scramble. With ReDuX, state agencies can modernize incrementally today to ensure scalability, resilience, and real time processing tomorrow.

If your agency is ready to move beyond stabilizing your UI system and start modernizing for scalability, resilience, and real-time processing, contact us to schedule a live demo with our team.

This year Karsun achieved not one, but two AWS competencies: AI Services and Mainframe Modernization. We are committed to continuous innovation and these are our fourth and fifth competencies, joining recognition of our work as a Government, DevOps, and a Migration and Modernization solution provider. Each competency represents proven experience delivering those solutions on AWS and proven expertise through professional certifications.

AWS competencies have benefits for our customers and team members alike. It also reinforces our commitment to training and retaining AWS certified team members. At Karsun both our remote and hybrid team members have access to Karsun Academy, our professional development program, and the Karsun Innovation Center, our in-house Research and Development (R&D) team. Together they provide virtual bootcamps, subsidized certification programs, monthly Innovation Town Halls featuring real-life technology solutions from our teams, and workshops where we bring industry experts directly to our Karsun teams.

And the best part is we’re hiring! Check out our hot jobs below and join the company where our team members Find Their Next. For the complete list of job openings, visit KarsunCareers.com.

Karsun Hot Jobs for Summer 2026

• Chief Solution Architect – https://www.karsuncareers.com/jobs/3651?lang=en-us
• Lead Full Stack Developer – https://www.karsuncareers.com/jobs/3693?lang=en-us

Five Fast Facts About Growing as an AWS Practitioner at Karsun Solutions

1. Karsun offered over 8200 hours of training to our team members in 2025.
2. Karsun’s AI, Mainframe, Migration, and Cloud Solutions work is accelerated by our ReDuX AI Platform. Using ReDuX teams deliver 4 times faster with half the rework.
3. In addition to its AWS competencies Karsun is an AWS Well-Architected, Immersion Day, and Public Sector Partner. It is also an AWS Transform Co-Innovation Partner.
4. Karsun cloud experts deliver cloud solutions to U.S. government agencies and mission-driven organizations.
5. We are proud members of the AWS Partner community. Follow us on LinkedIn and discover where we’re headed next!

Join our innovative, award-winning organization. In case you missed it, the Washington Business Journal recently listed Karsun Solutions among the largest employers in the Washington, D.C. region. Not only that, but WTOP named Karsun one of the Top Workplaces in D.C. In fact, in addition to these awards in the D.C. area. Karsun has repeatedly ranked among the best employers in the USA, in Oklahoma City, and among companies hiring remote employees. Moreover, our culture drives innovation, an insight we shared in a blog here.

And now, we’re growing again! Karsun is hiring. Take the next step in your career journey and check out our latest hot jobs below. Follow us on LinkedIn for the latest news from our team!

Our Latest Technology Hot Jobs:

• Chief Solution Architect: We are seeking a technical visionary to reimagine the transformation of legacy applications using traditional architecture combined with low code application platforms (LCAP) and AI/ML technologies.
• Lead Full Stack Developer: Grow an agile team of developers and test automation into a high-performance team.

Meet Karsun Solutions

Launch the next step in your career with the company transforming possible for government agencies. Join the workplace where the only limit on your potential is the limit of your curiosity. Find Your Next with a company focused on flexibility, professional excellence and innovation. 

Five Fast Facts About Working at Karsun:

• Karsun modernization experts deliver modern software, cloud, data, and AI solutions to government agencies.
• Our work is powered by the ReDuX platform which uses agentic AI to rapidly blueprint and transform complex legacy systems. See it in action at GoReDuX.ai.
• Our customers include the General Services Administration, Federal Aviation Administration and other federal agencies.
• Karsun was recently named a Public Sector Contender by ISG. 
• Karsun offered over 8200 hours of training to our team members in 2025.

Discover our latest openings at KarsunCareers.com.

While some states are modernizing to reduce costs, others are being driven by a different challenge, improving how government services are experienced by the people who use them. In 2026 constituents expect digital interactions with the government to feel no different than digital interactions anywhere else. They expect services to be intuitive and available when they need them.

Research from Georgetown University’s Beeck Center for Social Impact and Innovation’s DigitalGovHub shows that states are increasingly investing in digital transformation to improve service delivery. Better service delivery is not separate from efficiency. In many cases, improving how services are delivered is what drives efficiency.

Expectations Have Changed

The standard for government services has shifted. People no longer compare public services to other agencies. They compare them to every other digital experience they have. Whether while applying for benefits or updating records, users expect those interactions to be simple and consistent. According to StateScoop, the National Association of State Chief Information Officers (NASCIO) reported that digital services are now among the top priorities for state leaders.

This reflects a broader realization that digital experience is no longer just a technology issue but is becoming a trust issue. When services feel difficult to access, the government feels harder to trust.

Why Legacy Systems Cannot Deliver Modern Experiences

Legacy systems were not built for today’s user experience. Many still rely on outdated interfaces, disconnected databases, and siloed workflows that make it difficult for systems to communicate effectively or share information seamlessly across agencies. As a result, users are often forced to repeat information, move between systems, or wait through delays that feel unnecessary. That creates frustration for constituents and inefficiency inside agencies. Every confusing process adds manual work and places more pressure on internal teams. Over time, poor digital experience becomes an operational problem instead of just a customer experience problem.

This is where many states are now seeing modernization differently. Improving digital services is not just about making systems easier to use. It is about reducing the operational burden those systems create.

Better Experience Creates Better Efficiency

States that improve service delivery often see internal benefits at the same time. When systems are easier to navigate, users complete tasks more accurately. When services are connected, staff spend less time correcting errors. When processes are automated, agencies can focus resources on more complex work instead of repetitive tasks.

The result is that better experiences often lead to more efficient operations. This is why digital experience is becoming a strategic priority as it is about building systems that reduce friction across the entire organization. As both Pew and NASCIO suggest, agencies are increasingly recognizing that user experience and operational efficiency are deeply connected.

A More Citizen-Centered Approach

One of the more important shifts happening in 2026 is how states define service delivery. Instead of designing systems around agency workflows, more states are beginning to design services around how people actually interact with the government. That means creating simpler experiences, connecting systems behind the scenes, and continuously improving services based on real user needs. That shift changes modernization from a technical exercise into a service strategy that may be the more meaningful transformation for many agencies. 

Moving Forward with Confidence

Digital experience is becoming one of the strongest drivers behind modernization. Platforms like Karsun’s ReDuX help agencies better understand the systems behind their services, identify where friction exists, and modernize in a way that improves both usability and efficiency. By creating a clearer path from legacy systems to connected experiences, agencies can improve service delivery without increasing complexity.

To learn how agencies are modernizing digital services, explore our latest case studies or connect with our team to discuss how these strategies can be applied in your organization.

State agencies entered 2026 with a familiar challenge: rising expectations constrained by shrinking budgets. Agencies must deliver better services, move faster, and remain secure, all while operating with fewer resources. That pressure changes how states think about modernization. What was once positioned primarily as a long-term technology investment is now being evaluated based on its ability to deliver near-term operational and financial improvements. 

Research from Pew shows that states are doubling down on efficiency and technology innovation as budgets tighten. This shift is already producing measurable results. Maryland, for example, modernized parts of its vehicle fleet operations and expects to save approximately $800,000 annually while Pennsylvania, having taken a similar approach, saved tens of millions of dollars.

States are no longer modernizing simply to replace aging systems. They are modernizing because efficiency has become a financial necessity.

Legacy Systems Are Standing in the Way

Many agencies are trying to improve efficiency using systems that were never designed for this level of demand. Insights from StateScoop show that states are shifting toward technologies like artificial intelligence to automate work and improve operational efficiency. At the same time, the National Association of State Chief Information Officers (NASCIO) continues to highlight digital services and cybersecurity as top priorities.

Legacy systems make that balance difficult. Financial data is often siloed, limiting visibility into spending and making it harder to identify fraud and waste. Manual processes slow reporting and force agencies to react to problems rather than prevent them. This lack of visibility and automation impacts both efficiency and experience. Without real-time insight into operations, agencies struggle to identify inefficiencies early, and staff are forced to rely on time-consuming, manual workflows. 

Fortunately, legacy modernization can solve many of these concerns. For example, one Karsun team addressed this challenge with the development of a dashboard for one of our federal customers. By improving transparency the customer improved accountability across IT investments. By centralizing data and improving visibility into spending and performance, they could more easily track outcomes, identify inefficiencies, and make more informed decisions. 

Cost Optimization Is Becoming a Strategic Priority

Agencies face another challenge with their aging systems. Legacy systems become more costly to maintain and increasingly difficult to support as expertise declines. The longer they remain in place, the harder it becomes to operate efficiently and respond to changing demands.

For many states, modernization is now directly tied to cost control. Rather than making broad changes all at once, agencies are focusing on improving financial visibility, reducing waste, and automating repetitive internal processes that consume time and resources. Modern systems enable this by providing real-time insights and reducing reliance on manual work, allowing agencies to manage resources more proactively. This shift also reflects growing pressure for accountability. As reported by StateScoop, political and budget constraints  are pushing agencies to justify spending more clearly. Modernization, in this context, becomes a way to reduce costs while improving transparency.

A Shift Toward Measurable Results

States are also redefining how they approach modernization. Instead of large, multi-year efforts, agencies are prioritizing initiatives that deliver measurable outcomes such as cost savings and improved operational performance. As highlighted by both The Pew Charitable Trusts and National Association of State Chief Information Officers, modernization is increasingly tied to efficiency, not just innovation.

Moving Forward with Confidence

Cost optimization is only one part of the modernization story. Many states are also focusing on improving how services are delivered, recognizing that better experiences can also drive efficiency. We will explore this shift in more detail in the next blog.

Platforms like Karsun’s ReDuX help agencies better understand their systems, identify inefficiencies, and modernize in a way that reduces risk while improving visibility and control.

To learn how agencies are approaching modernization to improve financial performance, explore our latest case studies or connect with our team to discuss what that strategy could look like in your agency.

As organizations move from AI experimentation to real implementation, one thing is becoming clear: there is no single path to integrating large language models (LLMs). The way enterprises adopt AI depends heavily on where they start, whether that is application development, data infrastructure, or regulatory requirements.

At Karsun, we see this play out across customers. Instead of pushing a single solution, our focus is on helping organizations navigate this growing ecosystem of enterprise AI platforms and then select the approach that best aligns with their goals and mission. We work with many of  the most common enterprise AI platforms including Amazon Bedrock, Databricks Mosaic AI and Snowflake Cortex.

Two Ways Organizations Are Approaching AI

At a high level, enterprise AI strategies tend to fall into two categories. Some organizations prioritize speed and accessibility, adopting API-driven services that make it easy to integrate AI into applications. Others prioritize control and governance, embedding AI directly into their data platforms as part of a broader enterprise AI platform strategy. I like to think of this as a spectrum, ranging from a high-end all-you-can-eat buffet to a custom Michelin-star kitchen. Some enterprise AI platforms are designed for speed and flexibility, allowing teams to quickly access a variety of models and get started with minimal overhead. Others are built for control and customization, enabling organizations to tailor models, workflows, and governance to their specific data and requirements. 

Neither approach is inherently better. They reflect different priorities, and in many cases, organizations are starting to use both, aligning each approach to the specific problem they are trying to solve.

Enterprise AI Platform for Speed and Optionality

Amazon Bedrock 

Amazon Bedrock represents a more application-layer approach to AI. It provides a fully managed, serverless enterprise AI platform that provides access to multiple foundation models through a single API, removing the need to manage infrastructure.

This allows teams to move quickly from experimentation to production. Developers can integrate AI capabilities, test across different models, and scale usage without needing deep expertise in model hosting or data engineering. Built-in guardrails and simplified retrieval-augmented generation workflows also make it easier to incorporate enterprise data while maintaining appropriate controls. For many organizations, especially those already operating in cloud environments, this becomes a practical way to introduce AI without significant overhead.

Enterprise AI Platform for Control and Customization

Databricks Mosaic AI

Databricks Mosaic AI reflects a different approach by embedding AI directly within the data platform. Instead of sitting on top of the stack, it becomes part of the broader data and analytics workflow.

This gives organizations tighter control over how models are built and trained. Teams can work directly with proprietary data and develop more customized solutions. It also supports more complex, multi-step AI systems that go beyond simple prompt-response use cases. For organizations where AI is deeply tied to data strategy, this type of enterprise AI platform is essential to delivering reliable and repeatable outcomes.

Snowflake Cortex

Snowflake Cortex represents another data-centric approach to enterprise AI by embedding AI capabilities directly within the data cloud. Similar to Databricks Mosaic AI, it focuses on bringing models closer to where enterprise data already lives. This allows organizations to run AI-powered functions directly within Snowflake using familiar tools like SQL and Python. Teams can apply LLM capabilities including classification and data enrichment without needing to move data outside the platform or manage additional infrastructure.

For organizations already invested in Snowflake, Cortex becomes a natural extension of their data strategy. It enables teams to integrate AI directly into analytics and reporting workflows while maintaining strong governance and control over sensitive data.

Built for Compliance and Change

For enterprise and government customers, these decisions are rarely just technical. Compliance, security, and regulatory requirements often play a central role in shaping AI architecture. Some organizations prioritize managed enterprise AI platforms with built-in guardrails to simplify compliance, while others require full control over their data and models to meet strict governance standards. Both approaches are reflected in platforms like Bedrock,  Mosaic AI, and Snowflake Cortex.As regulations evolve and model availability changes, organizations need the ability to adapt without being locked into a single provider or model. At Karsun, this is a key part of how solutions are designed. Our goal is to help customers build AI systems that align with their compliance frameworks while remaining adaptable over time.

Connect with our team and learn more about Karsun’s AI solutions to see how these enterprise AI platforms can be applied to your organization’s needs.