What if your healthcare benefits application was processed instantly, even during peak enrollment seasons?
The global automation market is growing, where efficiency drives progress. It has been estimated that businesses worldwide can generate $15.7 trillion in value through AI and automation by 2030, per PwC analysis. Still, many challenges come up with the rising demands of automation.
According to Forbes research, 70% of digital upgradation initiatives by companies miss their goals, which has given rise to an urgent need for fast and reliable systems across sectors like government and healthcare.
To tackle these challenges on a global scale, Kiran Macha, a Robotic Process Automation (RPA) and cloud solutions expert, came up with some noteworthy solutions. Blending RPA with cloud technology, he worked on innovative projects that reshaped government operations, particularly in Medicaid, unemployment claims, and healthcare benefits enrollment. Passionate for developing systems that work smarter, he has experienced firsthand that the right tools and methods can boost public service delivery and equity.
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Outdated processes slow down everything; this is a tough reality faced by government agencies worldwide. In the public sector, especially healthcare and social services, agencies handle massive volumes of data, from benefit applications and eligibility verifications to claims processing and audits, which is mostly handled manually or with outdated systems. According to a 2021 analysis, inefficient administrative processes in U.S. healthcare alone cost $265 billion annually, while delays in benefits enrollment leave millions waiting weeks or months for critical support.
During peak periods like open enrollment seasons or economic downturns with surging unemployment claims, systems overload, leading to backlogs and frustrated citizens. Also security risks are large, with data breaches in healthcare averaging $9.77 million in 2024, per IBM’s report, and strict compliance requirements like HIPAA adding complexity. Additionally lack of scalability means firms can’t grow without rebuilding their entire setup, as it is a costly move for resource-strapped public entities. These problems not only strain budgets but also exacerbate societal inequities, delaying access to vital services like Medicaid coverage or unemployment aid. This calls for a solution that is safe, scalable and accessible.
Kiran Macha, an architect of automation solutions, is driven by a goal to create technology for all, not just the big names. With over 9 years of experience in software development and 8 years specializing in designing RPA systems and cloud infrastructures, he has worked on projects that help serve government industries like healthcare and social services. One project that stands out was managing chaotic data flows in healthcare benefits enrollment, a common pain point for state agencies worldwide. As enrollment volumes spike, manual reviews lead to errors, delays, and incomplete decisions, there is no proper system to manage the chaos. To handle such scenarios, Kiran came up with a plan that could tackle this problem, with an aim to benefit not just one agency but entire public service ecosystems.
The project started by identifying the weak links, such as slow eligibility determinations, data mismatches across systems, and overwhelmed staff during enrollment surges. He designed a hybrid system where RPA bots automated routine tasks like data extraction from applications, form validation, and initial rule-based decisions, while cloud integration and GenAI enabled intelligent handling of complex cases. With this, Kiran not just wanted to fix a problem, but to devise a model that others could follow. His approach reduced delays in benefits processing across states, cutting wait times for vulnerable populations and promoting equitable access to healthcare.
A key motive of this was making the system adaptable, where he introduced self-tuning systems by using GenAI for cognitive decision-making, allowing the setup to interpret nuances in unstructured data like varying income proofs or employment histories, without constant human input. The project impacted society by accelerating approvals for Medicaid and unemployment benefits, especially in underserved communities where timely aid can transform lives. It also enhanced compliance and reduced administrative waste, aligning with goals for efficient, transparent government operations. His philosophy behind this solution is as unique as his contributions. He says, “I wanted to create something that doesn’t just solve today’s problems, but grows with the needs of the world.”
Kiran’s solution was a blend of advanced tools and smart design, where he leveraged RPA platforms like Power Automate and Automation Anywhere to automate repetitive tasks, such as scraping text from healthcare applications, auditing data across state systems, and generating audit logs. This was bolstered by AWS cloud services for scalable backend support. The architecture included serverless functions via AWS Lambda for event-driven processing, SQS and SNS for reliable messaging, and DynamoDB as a NoSQL engine to handle unstructured data from diverse sources, which is a frequent issue in government workflows. GenAI integration, using pre-trained models on domain-specific data, provided enhanced decision-making, breaking free from rigid if-else logic to assess eligibility factors like wage variations or local conditions. This resulted in a 30% improvement in processing speeds for complex cases, benefiting high-volume enrollment periods. Security was strengthened with encrypted data flows and compliance tools, lowering breach risks by aligning with HIPAA standards and lowering error rates in sensitive healthcare data handling.
The AWS backbone utilized scalable compute resources like EC2 and Load Balancers, along with storage via S3, enabling the system to expand seamlessly during peaks without downtime. Kiran integrated monitoring via CloudWatch, slashing oversight efforts and allowing teams to focus on policy rather than troubleshooting. Paired with real-time analytics, the NoSQL setup processed 50% more applications than legacy systems, helping agencies predict loopholes and prevent backlogs. This technical advancement supported 30% more transactions during enrollment seasons, decreasing citizen complaints by 25% based on internal metrics and saving thousands of hours yearly, such as 9,600 hours in one Workforce Management project and 6,800 hours in Michigan premiums reviews.
On a broader scale, the effects were profound as state agencies in resource-limited areas gained affordable tools, which were previously out of reach. This sped up access to benefits like food assistance and medical coverage. In remote or low-income regions, faster processing improved health outcomes and economic stability. An energy-saving design reduced carbon footprints by 10% per operation, supporting sustainable public services. Underscoring the human side of his work, he says, “Seeing how technology reaches people who need it the most, keeps me motivated.”
This project showcases how smart automation can bring a positive change in the world, not just the efficiency gains. By merging RPA, GenAI, and AWS innovation, Kiran Macha has developed a framework that addresses public sector challenges like delays, compliance, and inequities while advancing government operations in healthcare and social services. With processing boosts of 80% and oversight reductions of 40%, the outcome is quicker, more equitable access to benefits and a more responsive future. This work presents a blueprint for others, showing that technology can serve society and bring about a lasting change.
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