Category: Uncategorized

TechSur Solutions Ascends: Our Inclusion in the GSA MAS 8(a) Sole Source Pool

We are thrilled to announce that TechSur Solutions has been formally added to the GSA MAS 8(a) Sole Source Pool! This allows federal agencies the ability to Multiple Award Schedule sole source 8(a) orders with us. For those unfamiliar with the GSA MAS 8(a) Sole Source Pool, it’s a program designed by the General Services Administration (GSA) to streamline the procurement process for Federal agencies. Essentially, vendors can receive direct contract awards without the typical prolonged competitive bidding process.

Benefits to You:

– Speedy Deployments: As we can swiftly respond to immediate governmental needs, our clients can benefit from expedited project kick-offs and timely solutions.

– Versatility in Service: With eligibility for both sole source and competitive 8(a) awards, TechSur Solutions offers a wider range of services tailored to fit diverse governmental requirements.

– Reaffirmed Credibility: Being vetted and included in this program reiterates our commitment and proficiency in delivering emerging technology and digital transformation services.

Stay tuned to our “News & Insights” for more updates, industry insights, and technological breakthroughs.

Achievement Unlocked: Inc. 5000 List!

Thrilled to announce our placement on the 2023 Inc. 5000 list! The Inc. 5000 is a ranking that highlights the fastest-growing private companies in the United States. It’s a reputable list and we’re pleased to be part of it. We are not just growing, but we’re keeping pace with some of the most rapidly developing companies in the country.

We would like to express our gratitude to everyone who has played a role in our journey so far. This includes our dedicated team, partners, and our customers who trust us with their enterprise needs.

Let’s continue to #MakeSomeNoise!

Adopting Agile Practices: A Key to Modernizing Legacy Systems

The digital revolution has necessitated that organizations adapt and evolve to maintain a competitive edge. A key aspect of this involves the modernization of legacy systems, particularly in Federal government organizations. These organizations grapple with aging infrastructure that struggles to meet modern standards of efficiency, performance, and security. 

In fact, each year, the Federal government spends over $100 billion on IT, with approximately 80 percent of this budget allocated toward the operation and maintenance of existing IT investments, including these aging legacy systems. 

Agile practices, known for their flexibility and efficiency, can act as a catalyst in this modernization process. Agile methodologies are an approach to project management, predominantly in software development, where tasks are divided into small phases of work and reassessed through frequent iterations or sprints. By prioritizing flexibility and customer feedback, Agile methods enable teams to quickly adapt to changes, ensuring the end product meets the evolving needs and expectations of the customer. Here’s more about the crucial role Agile plays in maintaining and then revitalizing these legacy systems.

Agile Practices and Legacy System Modernization

In 2019, the US Government Accountability Office (GAO) conducted an assessment of federal legacy systems and identified ten critical systems that require urgent modernization. Some of these systems have origins dating as far back as the 1970s. In total, the inventory included 65 identified systems, a significant portion of which still rely on legacy programming languages like COBOL. While these legacy systems have demonstrated dependability over time, they present a range of formidable challenges that need to be addressed, including the following:

  • There are escalating maintenance costs associated with outdated technologies and a scarcity of resources with expertise in maintaining these systems.
  • The inflexibility of legacy systems makes it difficult to adapt to changing business requirements. 
  • Compatibility issues also arise when attempting to connect these systems with newer platforms and applications.

To tackle these challenges, Agile methodology offers a flexible and iterative approach to project management and software development. It emphasizes adaptability, customer collaboration, and responsiveness to change. Applying Agile principles to the modernization of legacy systems can yield several benefits. By adopting Agile practices, organizations can introduce a continuous improvement mindset, enabling regular upgrades and enhancements to these systems. This iterative approach allows for the identification and resolution of issues in a more timely manner, leading to optimized functionality and improved performance.

Role of Agile Practices in Facilitating System Upgrades

In the year 2020, an examination of federal agency expenditures revealed that approximately $29 billion was attributed to the expenses associated with maintaining legacy IT systems. These legacy systems require regular upgrades to keep pace with technological advancements and evolving business needs. Agile methodologies have emerged as a crucial factor in facilitating these upgrades, with continuous integration and delivery being core tenets of Agile practices.

A notable example illustrating the benefits of Agile implementation in the government sector is the Federal Aviation Administration’s (FAA) Navigation system update. The FAA leveraged Agile practices to incrementally introduce improvements to the system, thereby minimizing disruptions while enabling regular feedback and adjustments. This iterative approach allowed the FAA to enhance the system’s functionality in a controlled manner while ensuring its alignment with ever-evolving industry standards. With Agile methodologies, the FAA successfully navigated the complexities associated with system upgrades, delivering a more robust and efficient Navigation system for aviation stakeholders.

Enhancing System Maintenance through Agile

Incorporating Valuable Feedback

One of the key advantages of Agile methodologies in legacy system maintenance is the emphasis on continuous feedback. By actively engaging stakeholders, including end-users and system administrators, in the maintenance process, government organizations can gather valuable insights and identify areas for improvement. Agile practices encourage regular and open communication, enabling quick identification of issues and prompt resolution. This iterative feedback loop allows for continuous improvement and ensures that the maintenance efforts are focused on addressing the most critical concerns.

Resource Efficiency with Incremental Development

An Agile approach promotes iterative development, which is particularly beneficial for legacy system maintenance. Instead of attempting large-scale and time-consuming updates, Agile encourages breaking down maintenance tasks into smaller, manageable increments. This approach leads to a more efficient allocation of resources and minimizes the risk of disruptions or system downtime. By continuously delivering incremental updates, government organizations can ensure that high-priority tasks are addressed promptly, reducing the impact on system performance and reliability.

Agile Transformation in USCIS Electronic Immigration System

As an illustration, the U.S. Citizenship and Immigration Services (USCIS) implemented Agile methodologies in the ongoing evolution of their Electronic Immigration System, with various teams collaborating to deliver these methodologies. TechSur helped implement Agile practices for USCIS on one of the later delivery teams. This project as a whole focused on the digital transformation of two high-traffic services: the Form I-90 application for replacing a permanent resident card and the USCIS Immigrant Fee Payment platform. Together with other team members, TechSur facilitated the phased launch of these services, following Agile principles.

Within the Agile framework, daily releases of system updates and enhancements were used to execute the project. Actively engaging with users, seeking their valuable feedback, and conducting consistent usability tests to identify areas for improvement all led to project success. By actively participating in these processes, USCIS realized constant system improvements, prompt problem-solving, and enhanced user satisfaction. 

Overcoming Resistance and Barriers to Agile Adoption

Implementing Agile methodologies in government settings can sometimes encounter resistance, primarily driven by factors such as a culture of rigidity, fear of change, or a lack of Agile expertise within the organization. However, there are notable examples of successful Agile implementation, including the U.S. Department of Defense (DoD). The DoD encountered challenges during its transition to Agile practices but overcame them effectively.

Overcoming resistance to Agile implementation in government settings necessitates a multifaceted approach. Building Agile awareness among the stakeholders and decision-makers is crucial. This involves educating them about the principles, benefits, and potential outcomes of Agile methodologies, enabling them to understand its relevance and potential positive impact on government operations.  Organizations can foster a culture of collaboration and adaptability while encouraging stakeholders to embrace change and actively participate in Agile processes.

Investing in Agile training and coaching can equip government employees with the necessary skills and knowledge to adopt Agile practices successfully. Training programs may cover Agile frameworks, project management techniques, effective communication, and team collaboration. Comprehensive training enables government organizations to empower their workforce to embrace Agile principles and methodologies, enabling them to adapt to changing requirements and deliver projects more efficiently.

Conclusion

The drive towards digital transformation mandates the modernization of legacy systems, particularly in Federal government organizations. With an iterative, flexible approach, Agile practices offer a powerful mechanism to drive this modernization. By facilitating regular system upgrades, enhancing maintenance processes, and overcoming adoption barriers, Agile can significantly boost these systems’ performance, efficiency, and longevity.

As we look towards the future, the importance of Agile practices will only increase, promising more efficient, effective, and adaptive government organizations. Consequently, adopting Agile practices should be prioritized to fully leverage their potential in revitalizing legacy systems and transforming governmental digital infrastructure.

Ready to embrace Agile for legacy system modernization? Trust TechSur as your Agile transformation partner for future-proof government solutions.

 

Using Machine Learning to Flush Out Money Launderers

Money laundering continues to pose a significant challenge, necessitating innovative approaches to combat this illicit activity. Globally, the estimated annual amount laundered falls within the range of 800 billion to 2 trillion dollars

Remarkably, the United States alone contributes at least $300 billion to this total, signifying its responsibility for a substantial portion, ranging from 15% to 38%, of the annual global money laundering volume. Hence, financial institutions are increasingly turning to machine learning and advanced customer risk-rating models to strengthen their defenses against money laundering. 

This article explores the benefits of adopting machine learning algorithms in identifying and flushing out money launderers. Government agencies play a crucial role in combating financial crimes. They can enhance their capabilities and safeguard the financial system by leveraging these technologies.

 

The Power of Machine Learning in Money Laundering Detection

Despite a high imprisonment rate of 91.1% for money laundering offenders, a staggering 90% of money laundering crimes go undetected. To address this challenge, the implementation of machine learning (ML) proves crucial. ML algorithms and advanced data analysis techniques help government agencies detect and prevent money laundering. They identify complex patterns and anomalies in vast financial datasets. Authorities can leverage ML to enhance capabilities, strengthen the fight against money laundering, and ensure a safer financial system.

 

1. Simplified Model Architecture

Machine learning enables organizations to simplify the architecture of their customer risk-rating models. Machine learning models utilize detailed, behavior-focused data to develop advanced algorithms, offering greater flexibility and adaptability to evolving trends. These models outperform traditional rule-based and scenario-based tools, continually enhancing their performance over time. According to McKinsey, a prominent financial institution experienced significant improvements by transitioning from rule-based approaches to machine learning models, achieving up to a 40 percent increase in the identification of suspicious activities and up to 30 percent efficiency gains. This highlights the substantial benefits of leveraging machine learning in combating illicit financial activities. Additionally, a streamlined approach like this enhances operational efficiency and reduces false positives, allowing agencies to focus their resources on high-risk cases.

 

2. Improved Data Quality

Effective money laundering detection relies on high-quality data. Machine learning techniques enable organizations to enhance data quality through automated data cleansing and validation processes. By leveraging these capabilities, government agencies can ensure the accuracy and reliability of their data. Subsequently, this can lead to more precise risk assessments and better-informed decision-making.

 

3. Statistical Analysis and Expert Judgment

A prevalent obstacle in transaction monitoring and anti-money laundering (AML) processes is the generation of a significant number of suspicious activity alarms. It is estimated that only a mere 1-2% of these alerts actually represent genuine threats, leaving the remaining 98% categorized as false positives. 

In contrast, machine learning uses expert judgment with statistical analysis, offering a powerful combination of human expertise and data-driven insights reducing the number of false positives by a significant degree. By incorporating statistical analysis into the risk-rating models, government agencies can utilize both quantitative and qualitative factors to identify potential money laundering activities. 

 

4, Continuous Customer Profiling and Behavioral Analysis

Machine learning algorithms allow for continuous customer profiling, taking into account evolving behaviors and patterns. Government agencies can monitor and analyze customer behavior in real-time to detect anomalies and deviations indicative of money laundering activities. As a result, this dynamic approach ensures that risk assessments remain up-to-date and adaptable to changing circumstances.

 

5. Harnessing Network Science Tools

Machine learning, coupled with network science tools, empowers agencies to uncover intricate money laundering networks and identify key nodes within these networks. This enables government agencies to gain valuable insights into the structure and dynamics of money laundering operations by analyzing complex relationships and connections. This knowledge aids in proactive investigations, targeting not only individual actors but also the broader networks involved.

 

Conclusion

Machine learning algorithms offer immense potential for government agencies in their fight against money laundering. Adopting these advanced techniques, agencies can streamline their detection efforts, improve data quality, and harness the power of statistical analysis and behavioral profiling. Embracing machine learning empowers government agencies to stay ahead of money launderers, protect the integrity of the financial system, and preserve public trust.

Discover how advanced ML algorithms can revolutionize your money laundering detection efforts. Get in touch with TechSur to learn more and stay one step ahead in safeguarding against financial crimes.

Defense Against Government Fraud Using Data Analytics

Government fraud is a major concern for federal agencies, contributing to immense monetary losses and compromising public confidence. However, the introduction of contemporary data analytics technologies has become a powerful instrument in the battle against fraud and abuse of information. This article investigates data analytics’ transformational potential and its application to federal government entities. These agencies may dramatically improve their capacity to detect, prevent, and mitigate fraudulent actions by using the power of big data analytics, protecting public monies, and enhancing overall governance.

 

The Growing Threat of Government Fraud

According to recent research, illicit activities constitute a large amount of government expenditure, resulting in immense fiscal losses each year. Based on Federal Trade Commission data, consumer-reported fraudulent activity surpassed $8.8 billion in losses last year, a significant increase of over thirty percent over the previous year. 

The trend offers a devastating insight; if not controlled, the total loss may exceed by the end of 2023. These setbacks have consequences not just on governmental budgets but also on the execution of key services to residents. To combat this persistent issue, federal government entities must use proactive data analytics-enabled solutions.

 

The Promise of Data Analytics in Combating Government Fraud

1. Enhanced Detection Capabilities

Data analytics allows federal agencies to process vast amounts of structured and unstructured data, such as financial transactions, procurement records, and citizen data. By leveraging advanced analytics techniques such as machine learning and anomaly detection, government agencies can identify patterns and anomalies. These indicate fraudulent behavior. This proactive approach empowers agencies to detect fraudulent activities more swiftly, ensuring timely intervention.

Various research papers illustrate that with the increasing diversity of analytical tools, ‌strategic analysis can be done more extensively. A comprehensive examination can be conducted, encompassing various factors such as threats, vulnerabilities, risks, evolving trends in fraud phenomena, market dynamics, demographic aspects, fiscal policies, and the economic trajectory of entities. The analysis will encompass both the internal environment, considering vulnerabilities and institutional capabilities, as well as the external context, evaluating potential opportunities and threats. 

 

2. Real-time Monitoring and Predictive Insights

The Association of Certified Fraud Examiners’ Report reveals that by adopting proactive data monitoring, organizations can effectively reduce their fraud losses by an average of 54% and expedite the detection of scams by half the usual time. With real-time data analytics, federal agencies can monitor transactions and activities in near real-time, enabling prompt identification and prevention of fraudulent behavior. 

Agencies obtain significant predictive knowledge by employing big data analytics, enabling them to prepare for fraud threats and distribute resources appropriately. The preventive strategy reduces monetary losses and serves as a deterrent, thwarting potential scammers and preventing further damage.

 

Practical Implementation Strategies for Federal Agencies

Encouragingly, many government agencies have made notable progress in addressing fraud, waste, and abuse impacts. They use advanced analytics to identify unmeasured losses and enhance prevention and mitigation efforts. While establishing the necessary organizational framework and acquiring the essential skills may present challenges, the successful implementation of these initiatives can yield significant returns on investment, with ratios ranging from 10:1 to 15:1. 

 

1. Building Analytical Capabilities

Federal agencies must make investments in developing strong data analytics features, which include qualified individuals, facilities, and sophisticated analytics technologies. Agencies may guarantee that data analytics conclusions are effectively incorporated into their decision-making procedures by cultivating a culture that values data. Cooperation with third-party collaborators, such as academics and industry professionals, may be extremely beneficial in building and improving analytical capabilities.

 

2. Establishing Cross-Agency Data Sharing

Government agencies often possess fragmented datasets spread across different systems and departments. Establishing mechanisms for secure data sharing and interagency collaboration is crucial to unlock the full potential of data analytics. By integrating data from multiple sources, agencies gain a comprehensive view of fraudulent activities. This helps uncover patterns and networks that may otherwise remain unnoticed.

 

3. Continuous Monitoring and Iterative Improvement

Data analytics initiatives should be treated as an ongoing process rather than a one-time effort. Agencies should establish a feedback loop that incorporates regular monitoring, evaluation, and continuous improvement of analytical models and techniques. By staying abreast of evolving fraud schemes and adapting analytics approaches accordingly, agencies can effectively respond to emerging threats.

 

Conclusion

For federal government agencies combating fraud, waste, and abuse, data analytics is a robust weapon. Agencies can improve their fraud detection, prevention, and response capabilities by leveraging the power of big data analytics. Federal agencies can achieve cost savings, preserve public finances, and strengthen public faith by investing in analytical capabilities. Cross-agency collaboration on data and a commitment to continual improvement are key. Adopting data analytics is not just an opportunity but also an imperative in a rapidly growing threat landscape.

Take your government agency’s defense against fraud to the next level with TechSur. As a trusted partner, we provide advanced technology solutions and expertise in data analytics to empower agencies in combating fraudulent activities and safeguarding public funds. Discover how our cutting-edge tools can enhance your fraud detection capabilities, and visit our website to explore our comprehensive range of services. 

 

US Digital Service: Essential Building Blocks For Digital Scaling

Government agencies must overhaul their operations and services as we embrace the constantly changing digital age. Today’s citizens expect a hassle-free and seamless experience while using government services. 

According to an intriguing Brookings Institution survey, 51% of American residents prefer digital interaction with the government over face-to-face or telephone contact. 

Government organizations must adapt to the shifting environment. They need to continuously improve their digital products in order to fulfill the growing demand and expectations. It’s time to fully leverage digital transformation’s potential and improve the citizen experience. 

 

US Digital Service Establishing a Culture of Innovation

 In order for government organizations to undergo digital transformation, it is essential to establish an innovation-friendly culture. Many organizations have often come under fire for being bureaucratic and sluggish in adopting new technologies. However, the US Digital Service (USDS), which has been spearheading the drive for innovation culture in government institutions, has been particularly important in transforming this attitude.

Agile approaches and the principles of design thinking have been instrumental in driving change within government organizations, with the US Digital Service (USDS) at the forefront of this transformation. These guidelines place a higher priority on user demands and urge organizations to provide services that are more user-centric. Government agencies must collaborate closely with citizens and other organizations to understand their needs and pain points. This collaboration enables effective solutions and improved service delivery.

Agencies can produce more effective, efficient, and user-friendly services this way. Government agencies can recognize and handle the unique requirements and difficulties faced by their end customers. They can provide solutions that satisfy those requirements. For instance, firms can develop user-friendly websites, mobile applications, and other digital services. These services are designed using principles of design thinking to be simple to explore, comprehend, and use.

The USDS has pioneered this strategy. It encourages government organizations to experiment with cutting-edge tools like AI and machine learning. The goal is to enhance service delivery through innovative approaches. For instance, the USDS assisted the Department of Veterans Affairs (VA) in creating a program that uses AI to identify veterans who are at risk of suicide. This tool uses data from VA’s electronic health records system to identify those who may be at high risk of suicide. It then provides targeted interventions to prevent suicides.

 

Improving Digital Infrastructure

Government agencies must modernize their digital infrastructure in order to stay up with the rapidly changing digital world. This upgrade includes spending money on cutting-edge technology to increase data security, simplify processes, and improve user experience. 

Agencies can enhance their capacity to store and access data through cloud computing capabilities. They can also improve data analysis and decision-making processes. By adopting emerging technologies like AI and machine learning, agencies can automate repetitive operations, reduce errors, and generate valuable insights. These insights enable better decision-making and improve digital offerings.

According to a Gartner analysis, agencies are anticipated to embrace AI-augmented automation in their I&O teams, with a projected 40% utilization rate by 2023. This move is expected to boost IT productivity while also improving agility and scalability.
Modernizing digital infrastructure is a worthwhile investment for agencies. It improves efficiency, reduces costs, and enhances the user experience. It also meets the demands of modern-day citizens. This facilitates digital scaling in government by enabling agencies to adopt new technologies and innovate at a faster pace.

 

Streamlining Processes and Procedures

A McKinsey & Company report reveals that 60% of all occupations have at least 30% of their operations that could be automated, increasing agency productivity. 

The numbers show how automating government processes and procedures could have a positive influence. Agencies can enhance service delivery and save money. They can use this money towards other crucial initiatives by decreasing the workload on workers and minimizing errors.

Data-driven strategies have also shown to be successful in streamlining government procedures, in addition to automation. The city of New Orleans, for instance, implemented a data-driven strategy to reduce blight and improve the quality of life for inhabitants. The city was able to identify areas with high levels of blight and prioritize its efforts by looking at data on blight complaints and property violations. In just two years, the number of abandoned properties was significantly reduced in the city.

Through the application of data-driven techniques, federal agencies can identify opportunities for innovation and improvement by analyzing user feedback and behavior data to identify areas where they can enhance or expand digital services.

 

Conclusion

As the digital age progresses, government organizations must remain adaptive and innovative to meet the ever-changing needs of today’s citizens. Creating an environment that values innovation, investing in digital infrastructure, and streamlining procedures are essential for achieving digital scaling in government organizations. Prioritizing user needs and feedback, experimenting with emerging technologies, and embracing automation and data-driven techniques will enable agencies to enhance user experience, improve service delivery, and reduce costs. As we look ahead, the potential for digital transformation in government organizations is boundless. By embracing innovation, we can build a more connected, effective, and efficient government that empowers citizens and meets the challenges of the future.

Ready to take your government agency’s digital transformation to the next level? Contact Techsur Solutions today to learn how our expertise in building essential digital building blocks can help you achieve your goals.

Government Artificial Intelligence: Trade-offs and Conviction

Artificial Intelligence (AI) is more than just a buzzword, it’s a transformative technology that can revolutionize the way governments function and aid their citizens. With its capacity to automate tedious processes, analyze large volumes of data, and reinforce citizen engagement, AI has metamorphosed as a powerful tool for government agencies. But with great power comes great responsibility, and AI adoption in government is not without its challenges. Here is what to know about AI and government transformation, the challenges associated with AI adoption, and provide key considerations for federal government agencies and organizations looking to harness the potential of AI.

 

Opportunities of Artificial Intelligence in Government

1. Increased Efficiency and Productivity

Time-consuming and repetitive processes currently carried out manually can be automated by artificial intelligence. These include processing paperwork, examining applications, and performing audits. By doing this, government organizations can cut down on the time and money spent on these activities. This can free them up to concentrate on providing citizens with high-quality services. According to a Governing magazine research, 53% of the state and local officials surveyed reported they were overwhelmed with paperwork, which made it difficult for them to do their jobs effectively. On the other hand, according to Deloitte, automating jobs for federal government employees may save between 96.7 million and 1.2 billion hours of time annually. 

 

2. Improved Decision-making

AI can analyze vast volumes of data and produce insights that aid government organizations in making intelligent decisions. Agencies can use AI in various ways. For example, they can use it to forecast future demand for public services, recognize patterns in public health data, or investigate criminal activity. Government organizations can use their resources more effectively and offer citizens better services by utilizing these insights. 

 

3. Enhanced Citizen Engagement

A survey conducted by Accenture found that 63% of citizens would like to use AI-powered tools to interact with government agencies. This is because AI-powered chatbots and virtual assistants can provide citizens with 24/7 support and assistance. Citizens can use these chatbots to ask questions, submit requests, and receive information about government services. Government agencies can enhance citizen engagement and satisfaction by leveraging AI-powered chatbots. These chatbots use natural language processing capabilities to provide personalized and timely responses, improving the overall customer experience.

 

Challenges of Artificial Intelligence in Government

1. Algorithmic Bias

If artificial intelligence systems are trained on biased data, it may reinforce biases within the organization/agency. Some groups of people may experience unjust outcomes because of this. For instance, it was discovered that an AI-powered hiring tool created by Amazon was biased toward women. Governmental organizations must ensure that the data used to train AI models are diverse. These should also be inclusive of the entire community to prevent algorithmic bias.

 

2. Lack of Transparency

The use of AI in government can sometimes be opaque. This makes it difficult for citizens to understand how government makes its decisions. This lack of transparency can lead to distrust and undermine the legitimacy of government decisions. To address this challenge, government agencies must ensure that their AI-powered systems are transparent and explainable. This means that the algorithms used by these systems must be open to scrutiny. The decisions made by these systems must be explainable to citizens.

 

3. Ethical Concerns

Artificial intelligence raises ethical questions around issues such as privacy, consent, and accountability. For instance, the use of facial recognition technology by law enforcement agencies raises concerns about privacy and civil liberties. To address these concerns, government agencies must ensure that they design and implement their AI-powered systems in an ethical manner. Ethical principles must guide the development and deployment of AI systems, prioritizing the well-being and rights of citizens. This ensures accountability, fairness, and transparency in the use of AI technologies, protecting the interests of individuals.

 

Key Considerations for Federal Government Agencies

  • Align AI adoption with strategic goals: This requires federal government agencies to undertake a comprehensive strategic planning process that involves identifying specific business objectives and assessing the potential of AI to facilitate their attainment. Agencies must ensure that AI implementation is guided by a strategic and business-oriented perspective rather than an ad hoc response to technological trends or pressures. For instance, the Department of Agriculture (USDA) used AI in its analysis of crop data to enhance food production and sustainability, driven by a strategic goal of improving agriculture production while reducing environmental impact.
  • Develop a strong data management strategy:  This is critical for the successful implementation of AI in federal government agencies. Such a strategy must encompass robust data collection, storage, and analysis processes that support AI algorithms’ training and development while ensuring data security, privacy, and ethical considerations.
  • Ensure algorithmic fairness and transparency: Federal government agencies must ensure that their AI-powered systems are designed and implemented in a fair and transparent manner. This entails adopting explainable and interpretable AI models. These model can be subject to scrutiny and validation by stakeholders, including citizens, without compromising data privacy or confidentiality. Currently, the US Department of Labor’s Office of Disability Employment Policy has released guidelines for ensuring the fairness and transparency of AI-powered job matching systems to prevent discrimination against job seekers with disabilities. 
  • Invest in skills development and training: AI adoption requires specialized skills, which may not be readily available in government agencies. Federal government agencies must invest in the development of specialized technical competencies such as machine learning, data analytics, and natural language processing. They must also invest in non-technical skills such as critical thinking, problem-solving, and decision-making. 

 

Conclusion

The adoption of AI by federal government agencies has the potential to revolutionize how they operate and deliver services to citizens. AI offers the promise of increased efficiency, improved decision-making, and enhanced citizen engagement. It can be a key driver of transformation and innovation in the public sector. However, to fully realize the benefits of AI, federal government agencies must address the challenges associated with its adoption.By investing in ethical AI practices, federal government agencies can ensure responsible and accountable use of AI technologies. Additionally, prioritizing skills development can empower government employees to effectively leverage AI tools and technologies. Such a government will be better equipped to meet the diverse needs of its citizens, delivering improved services and outcomes. Adopting AI will allow agencies to usher in a new era of public service, ultimately transforming the lives of citizens for the better.

If you are a federal government agency or government organization seeking to harness the potential of AI to transform your operations, TechSur can help. Our team of experts has a deep understanding of AI technologies and can help you navigate the challenges associated with AI adoption in government. Contact us today to learn more about how we can help you unlock the benefits of AI.

Empowering the Emergency Management Workforce through AI and Machine Learning   

The world is becoming more unpredictable, with frequent and severe natural disasters, pandemics, and human-made crises. Besides the persistent global health crisis, the US has encountered an unmatched series of natural disasters in the past few years. Between 2016 and 2022, there have been 122 distinct disasters with damages exceeding one billion dollars each. Amidst this, emergency assistance and disaster recovery efforts are pushed beyond their limits. The traditional methods of emergency management are increasingly overwhelmed in the face of evolving threats and limited resources.  

 Artificial Intelligence (AI) and Machine Learning (ML) offer powerful tools to augment the capabilities of the emergency assistance workforce and improve the outcomes of disaster response and recovery efforts. The technology is improving at breakneck speeds. TechSur Solutions envisions and plans for a world where the Emergency Management workforce can use Grants Management systems that are fully optimized, secure, and efficient. AI/ML can empower Emergency Management agencies (such as the DHS Federal Emergency Management Agency) to make risk-informed decisions and respond rapidly to emergencies for a Prepared Nation.  

 

Applications of Artificial Intelligence and Machine Learning in Emergency Management 

Image: (December 14, 2021) MAYFIELD, Ky. — Louisville Emergency Management Director E.J. Meiman and Administrator Criswell discuss response operations near the Mayfield Consumer Products factory that was destroyed by a tornado late Friday. 

 The global market for incident and emergency management is projected to expand from an estimated USD 121.4 billion in 2022 to USD 163.6 billion by 2027, representing a Compound Annual Growth Rate (CAGR) of 6.2%. The market is expected to receive a significant boost from the escalating frequency of natural disasters worldwide. In these challenging times, AI/ML can play a role in enhancing emergency management efficiency in the following ways. 

 

Resource Allocation

AI can help allocate critical resources, such as food, water, and medical supplies, to the most vulnerable and impacted locations. In order to optimize resource allocation in real-time, Machine Learning may examine past data on resource requirements and consumption trends. Hurricane Harvey in 2017 was one event that led to the successful implementation of a similar strategy to locate vulnerable regions.

Disaster Response

Analysis of real-time data from numerous sources, such as social media, sensors, and satellites is possible with AI. This can help pinpoint regions of damage, gauge the impact, and set priorities for response actions. During the California wildfires, the WiFire Lab developed an AI system called BurnPro 3D that used real-time data to predict the spread of the fire, allowing firefighters to prioritize their efforts and adjust their strategies in real-time.

Recovery Efforts

Artificial Intelligence makes it easier to prioritize recovery operations based on the most pressing needs. It further helps estimate the cost of recovery and assess the extent of damage. For example, an AI system, xView2, analyzed satellite imagery to identify and estimate the extent of damage caused by the Turkey-Syria earthquake, allowing emergency responders to prioritize recovery efforts and allocate resources more effectively.

 

Benefits of Incorporating Artificial Intelligence and Machine Learning  

Image: JENNINGS, La. (Oct. 11, 2020) — FEMA Administrator Pete Gaynor talks about the whole-of-government response and recovery efforts after Hurricane Delta during an interview with The Weather Channel. FEMA photo by Jocelyn Augustino. 

 Integrating Al/ML into the training and skill enhancement of emergency management personnel can yield multiple advantages, including the following.

  • Improved Situational Awareness: Artificial Intelligence can give emergency management experts real-time alerts and insights. This  empowers them to make quick, well-informed decisions. 
  • Better Decision-Making: Machine Learning enables emergency management professionals to make data-driven decisions. It is possible by analyzing massive amounts of data and providing insights into patterns and trends. 
  • Efficiency Gain: AI can automate routine processes like data collection and analysis. This allows emergency management specialists to concentrate on life-saving duties. 
  • Reduced Risk of Human Error: In complicated and time-sensitive emergency management scenarios, such as resource allocation and response planning, AI can reduce the risk of human error. 

 

Successful Artificial Intelligence and Machine Learning Implementations in Emergency Management 

 DHS Federal Emergency Management Agency (FEMA) needed a resilient, modern system. This was crucial to evaluate each property and assess its flood risk based on data from hundreds of sources. They collected meteorological, geospatial, and other types of information. The agency gained valuable insights for faster and more accurate decision-making regarding flood insurance policies. TechSur Solutions created a modern, intelligent, DevSecOps-driven system for FEMA’s National Flood Insurance Program’s PIVOT program. Such experience empowers TechSur to take FEMA systems to the next level with our AI/ML expertise.  

 Here are a few examples of AI/ML solutions serving the Emergency Management sector:  

 

University of California & FEMA AI-Based System

Recent studies have demonstrated the potential of Artificial Intelligence and Machine Learning in enhancing disaster preparedness efforts. Artificial Intelligence can enable more precise predictions of the potential impact of a disaster on the affected population and infrastructure. AI specialists achieve this by analyzing and interpreting large amounts of data related to natural disasters. Artificial Intelligence can generate models that identify high-risk areas and recommend mitigation measures to minimize the impact of such disasters. An illustration of this is the AI-based system developed by researchers at the University of California, Berkeley, which increases accuracy in predicting the impact of earthquakes on buildings in California. The system employs machine learning algorithms to analyze seismic data. It provides comprehensive information about the anticipated intensity and duration of an earthquake. The extent of damage it would inflict on various types of structures can also be determined by the system.

Similarly, FEMA used machine learning to analyze data from social media and other sources to identify areas of damage and prioritize response efforts during Hurricane Maria in 2017. The analysis enabled FEMA to deploy resources more effectively and save lives. 

Copernicus Emergency Management Service

The European Union’s Copernicus Emergency Management Service uses Artificial Intelligence to analyze satellite images and other data to assess the impact of natural disasters, such as floods and earthquakes, and provide real-time information to emergency management specialists. The service has improved the speed and accuracy of response efforts and helped reduce the damage caused by disasters. 

UNDP’s MHEWS System

Currently, The United Nations Development Programme (UNDP) is developing a nationwide multi-hazard early warning system (MHEWS) in Georgia. The primary goal of this system is to reduce the exposure of communities, livelihoods, and infrastructure to weather- and climate-driven natural hazards. To achieve this, the MHEWS requires accurate forecasts and hazard maps of severe convective events, specifically hail and windstorms. The system will use AI/ML technologies to analyze data from various sources, such as weather stations and satellites, to provide timely and precise forecasts. It will also create hazard maps to identify the areas at the greatest risk. This would allow emergency management professionals to allocate resources more effectively and prioritize response efforts.  

 

Conclusion 

 

Artificial Intelligence and Machine Learning has enormous potential to empower the emergency management workforce. It can proficiently improve the outcomes of disaster response and recovery efforts. AI/ML enhances situational awareness, improves decision-making, increases efficiency, and reduces human error. This enables emergency management professionals to respond effectively to evolving threats and save lives. Federal government agencies and other organizations can greatly benefit from incorporating Artificial Intelligence and Machine Learning into their emergency management strategies and training programs.

TechSur Solutions leads AI/ML initiatives at several Federal agencies, including the Institute for Museum and Library Services (IMLS) (with an award-winning AI program) and DHS U.S. Citizenship and Immigration Services (USCIS). TechSur implements Artificial Intelligence at USCIS to predict operational issues before they occur to support users and improve immigration processing used by 19,000 government employees and contractors working at 223 offices worldwide. TechSur Solutions offers a comprehensive suite of services. This includes platform engineering, application modernization, and AI-driven analytics. These help transform Emergency Management Grants Systems into a secure, streamlined, and user-centric system that aligns with agency strategic goals. 

To learn more about how AI and machine learning can benefit your organization, contact TechSur, your agency’s partner in transforming emergency management. 

 

 

TechSur Solutions Awarded $34M+ TSO ITSS Contract to Develop Emerging Technologies at U.S. Courts

Herndon, VA – TechSur Solutions, LLC (TechSur) is pleased to announce an award in support of the Administrative Office of the United States Courts (AOUSC) Technology Solutions Office (TSO) for IT Support Services in emerging technologies and digital modernization, initially valued at $34M. This award was the first Prime contract for TechSur, a Small Business Administration (SBA)-certified 8(a) and Economically Disadvantaged Women Owned Small Business (EDWOSB) Small Disadvantaged Business.  

 

AOUSC’s Chief Technology Officer has established a roadmap for secure transformative technology for the next generation of cloud-native technology solutions. The mission of the TSO is to provide strategic vision and support to Courts and AOUSC Program Offices with modernizing technology critical to the Judiciary’s mission. TechSur supports TSO’s initiatives leading the Judiciary’s digital transformation through the establishment of technical standards, research and innovation efforts, and modernization consulting services. TechSur Solutions supports TSO’s collaborative efforts with Judiciary units to empower the implementation of innovative technologies and services to drive business-focused IT transformation. The immediate priorities are focused on assessments and implementation strategies for Enterprise DevSecOps, Enterprise Architecture, Identity, Credential and Access Management (ICAM), Cloud Migration, Hybrid Multi-Tenant Cloud Strategies, Enterprise Portfolio and Program Management, Agile Adoption, and Multi-Factor Authentication.  

 

Rupinder Yadav, President and co-founder of TechSur Solutions, says, “We are proud to have built on nearly 7 years of success and guidance under the SBA through their programs for women-owned companies to arrive at this point of readiness to help modernize the Courts.” 

 

About TechSur Solutions  

TechSur Solutions is an Emerging Technologies & Digital Transformation company serving Federal Enterprise customers since 2016. We deliver IT Services for Mission Platform Engineering (DevSecOps, Data Analytics, Cloud-Native Application Development), Hyper-Automation (Artificial Intelligence/Machine Learning, Robotic Process Automation), and Multi-Channel Digital Engagement (Website Design & Development, Strategic Communications). This SBA-certified 8(a) Small Disadvantaged Business (SDB) Economically Disadvantaged Minority Women-Owned Small Business (EDWOSB) was ranked by Washington Technology as the 7th fastest-growing small Government Contractor on their Fast50 List. In recent exciting news, an Artificial Intelligence solution delivered by TechSur Solutions to a Federal customer was awarded a Disruptive Technology Award! 

 

Contact 

info@techsur.solutions  

The Role of Hyper-Automation in Simplifying Grants Management Processes

Image: (March 24, 2023) The Smithsonian Institution and FEMA Co-host a Disaster Simulation for Protecting Cultural Artifacts.

Hyper-automation integrates diverse advanced technologies to automate and optimize complex Enterprise activities. Benefits of hyper-automation include the consolidation of operations, significantly reduced overheads, and enhanced overall efficiency. It leverages the power of Artificial Intelligence (AI), Machine Learning (ML), Robotic Process Automation (RPA), and other tools to automate repetitive tasks and minimize errors. Read on to discover how our expertise in platform engineering, application modernization, and AI-driven analytics can revolutionize grants management systems, streamline processes, and enable data-driven decision-making.

 

Potential Impact of Hyper-Automation on Grants Management 

Image: (February 14, 2023) A Mitigation Assessment Team (MAT) traveled to Florida to learn about Hurricane Ian’s effects on the built environment.

In the context of grants management, hyper-automation plays a pivotal role in expediting and simplifying the grant management process. Grants management covers a wide range of processes and activities, including application review, data entry, budget tracking, and performance reporting. By automating these activities, public sector organizations can not only save valuable time and resources but also augment the precision and effectiveness of the overall process.

According to a report by Gartner, the adoption rate of structured automation in organizations is expected to increase from 20% in 2021 to 70% by 2025. This trend of automating processes for improved operational efficiency is referred to as “hyper-automation” and is the next evolutionary step in this domain.

Hyper-automation can simplify the grants management process in the following areas:

 

1. Intelligent Document Processing 

 A recent study conducted by PwC discovered that employing even basic AI-powered data extraction methods can result in a reduction of 30–40% in the time typically dedicated to such procedures by organizations. Utilizing advanced AI and Optical Character Recognition (OCR) technologies, hyper-automation enables rapid extraction, classification, and validation of data from grant applications and supporting documents. This significantly reduces manual data entry errors and accelerates the review process, demonstrating the transformative potential of automation in managing grants.

 

2. Streamlined Budget Tracking 

 Through automating the monitoring of budgets and costs, organizations can achieve considerable time and resource savings. Robotic Process Automation (RPA) can be used to automate budget development and monitoring, ensuring that organizations stay within their spending limits and don’t go overboard.

 Consider a scenario where an agency has received a grant to fund a particular project. The agency is required to submit regular reports on the project’s progress and budgetary expenditures to the grantor. With the help of automation, the agency can automate the process of tracking and monitoring its budget. This can involve setting up a dynamic workflow that automatically aggregates data related to the project’s expenses and evaluates them against the financial stipulations of the grant, thereby optimizing budget management and compliance.

 

3. Improved Performance Reporting and Evaluation 

 Hyper-automation can streamline the reporting process by automatically aggregating, analyzing, and visualizing grant performance data in real time. This empowers organizations to evaluate the impact of funded projects, identify areas for improvement, and make data-driven decisions to enhance future grant-making strategies.

 

4. Predictive Analytics and Decision Support 

 By leveraging ML algorithms and data analytics, hyper-automation can generate predictive insights and recommendations to guide decision-makers in evaluating grant applications and allocating resources. This can optimize the selection process by identifying high-potential projects, avoiding possible risks, and ensuring funds are utilized effectively.

 

5. Compliance Monitoring and Risk Management 

 With the integration of AI/ML technologies, hyper-automation can continuously monitor grant recipients’ compliance with grant terms and regulatory requirements. By identifying discrepancies and potential risks early on, organizations can proactively address issues, ensuring the successful execution of funded projects.

 

Hyper-Automation and DHS Agencies  

Image (January 13, 2023) C-SPAN: U.S. Fire Administrator Lori Moore-Merrell Announces Launch of National Fire Strategy (FEMA Photo)

A study by Deloitte suggested that adopting cognitive technologies like artificial intelligence (AI) has the potential to streamline U.S. federal government office operations, potentially saving up to 25% of work hours and cutting costs by as much as $41 billion.

Streamlining and improving business performance for DHS agencies such as the Federal Emergency Management Agency (FEMA) is crucial for optimizing operational efficiency, resource allocation, and decision-making in response to natural disasters and other emergencies. By leveraging advanced AI through hyper-automation, these agencies can better optimize the grant application, review, and disbursement processes, reducing manual intervention and improving accuracy and efficiency.

Moreover, streamlining processes, such as budget monitoring and performance reporting, enables seamless communication and coordination among various stakeholders, including federal, state, local, tribal, and territorial partners, as well as non-governmental organizations and the private sector. Enhanced collaboration not only speeds up response times but also minimizes duplication of efforts and reduces administrative overhead.

Ultimately, optimizing performance using hyper-automation for agencies like FEMA is critical to safeguarding public safety, ensuring resilience in the face of emergencies, and promoting the efficient use of taxpayer dollars. Hyper-automation can simplify the grants management process, resulting in a Ready FEMA that is better prepared to serve the nation.

 

Real-World Example of Hyper-Automation in Grants Management 

The Institute of Museum and Library Services (IMLS), an independent agency of the U.S. Federal government, provides library grants, museum grants, policy development, and research. TechSur Solutions implemented Adaptive Artificial Intelligence (AI) to deliver solutions that meet IMLS current needs and continues to grow with their evolving needs. We integrate AI technologies to drive advanced automated tasks with actionable results from core business processes to the added-value chain.

The Institute of Museum and Library Services (IMLS) First Check review process was originally performed by Program Officers going through application files and databases to validate a grants application manually, taking up to 2 weeks. TechSur’s First Check tool reviews hundreds of applications in 1-2 hours and has been implemented as the initial reviewer for grant applications. The tool automates 95% of the First Check rules which allows Program Officers to focus on validating tool’s results and performing rule checks outside of the tool’s scope. An internal website is included in the tool as a centralized space for viewing, validating, and exporting First Check results.

TechSur and IMLS’ First Check program recently won a Disruptive Tech award, which recognizes Federal IT programs that are working every day to take calculated risks and positively disrupt the Federal market. We look forward to celebrating all 2023 award winners at the 2023 #DisruptiveTechSummit on April 12, 2023. http://bit.ly/426jGXg @FedHealthIT.

 

Conclusion 

To make hyper-automation work for grant management, it’s essential to have everyone on board and create systems that support your automation journey. Even more important is having the right know-how and a smart plan to adopt automation technologies in your organization. By doing this, public sector organizations can tap into the true power of hyper-automation and make grant management more efficient and effective.

 

Looking to simplify your grants management processes and improve efficiency through hyper-automation? Get started on the path to a smarter, more resilient Grants Management System. Contact TechSur Solutions today for a consultation and see how our innovative solutions can help you achieve your strategic goals.