🔒 Modernizing Grant Integrity with AI-Powered Fraud Detection

Proactively Combat Fraud, Waste, and Abuse in Public Funding

Billions in public funding are administered each year, yet traditional grant fraud detection methods—manual audits, rule-based checks, and random sampling—can’t keep pace with modern fraud schemes. The result? Delayed interventions, lost taxpayer dollars, and reduced public trust.

KRAI Solutions introduces an innovative, AI-powered risk scoring platform that uses machine learning to detect and prioritize potential grant fraud in real time. Built using secure, cloud-native AWS services, this solution transforms how federal, state, and local agencies approach oversight—moving from reactive audits to proactive fraud prevention.

Key Features & Capabilities

• Machine Learning-Based Risk Scoring: Uses XGBoost models trained on historical data to assign fraud probabilities to incoming grant applications.
• Cloud-Native Architecture: Built with AWS Glue, SageMaker, DynamoDB, and S3 for real-time inference, flexible scaling, and secure storage.
• Seamless Data Integration: Ingests and processes data from systems like Grants.gov, with automated cleansing and normalization.
• Secure and Compliant: Aligned with NIST SP 800-53, FedRAMP, and Executive Order 14028 to protect sensitive grant data.

Measurable Results

• 50% Reduction in Manual Review Burden
• Real-Time Scoring with High Accuracy and Precision
• Scalable Across Federal, State, and Local Agencies
• Audit-Ready Logs and Explainable AI Options (Coming Soon)

From detecting fraud before disbursement to generating audit-ready insights with Generative AI, our solution delivers intelligent, automated oversight at scale—supporting financial integrity and public trust.

Ready to Strengthen Grant Oversight with AI?

Contact us to explore how our fraud detection platform can modernize your agency’s approach to grant risk management..

🔒 Revolutionizing Federal IT with AI-Powered AWS CI/CD Pipelines

Secure, Scalable, and Compliant Application Deployment for Government Agencies

Federal agencies face growing pressure to modernize their IT infrastructure while maintaining strict compliance with cybersecurity mandates such as FISMA, NIST, FedRAMP, and Executive Orders like 14028. Traditional Authorization to Operate (ATO) processes slow down innovation and create bottlenecks in deployment cycles.

At KRAI Solutions, we've developed an AI-powered AWS CI/CD pipeline that integrates Continuous ATO (cATO) directly into the DevSecOps lifecycle—enabling real-time compliance, secure code delivery, and audit readiness without compromising speed.

Our cloud-native solution, built on AWS CodePipeline, features:

• AI-Driven Security Testing: Real-time secure coding guidance using SonarQube, OWASP, Snyk, and OpenAI.
• Automated Compliance Checks: Alignment with mandates like OMB M-22-18, M-22-09, and EO 14028.
• Scalable Multi-Cloud Integration: Designed for hybrid federal environments.
• Manual Approval Gates: Supports agency-specific governance workflows.

Case Study Highlight: In a successful deployment with our private partners, our solution enabled faster application delivery, continuous compliance, and seamless integration with legacy systems—without compromising on security or audit readiness.

Ready to Modernize Your Agency’s Software Delivery?

Contact us to learn how Krai Solutions can help your agency adopt a secure, compliant, and scalable DevSecOps pipeline tailored to federal requirements.

🔒 Loan Application Process Automation with AWS ML and UiPath

Many organizations start using Robotic Process Automation (RPA) to automate workflow and/or back-office processes that are labor-intensive.

In this post, we show how a financial institution can use a combination of UiPath and AWS ML services to automate a loan application process.

UiPath is a Robotic Process Automation platform for end-to-end high-scale automation. UiPath software offers solutions for enterprises to automate repetitive office tasks for rapid business transformation.

Robotic process automation (RPA) is a software technology that makes it easy to build, deploy, and manage software robots that emulate humans’ actions interacting with digital systems and software. Robotic process automation streamlines workflows, which makes organizations more profitable, flexible, and responsive. It also increases employee satisfaction, engagement, and productivity by removing mundane tasks from their workdays.

Amazon Textract is a machine learning (ML) service that automatically detects and extracts text and data from scanned documents. It goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables. Amazon Textract uses Optical Character Recognition (OCR) technology to automatically detect printed text, handwriting, and numbers in a scan or rendering of a document, such as a legal document or a scan of a book.

First, we show how to automate the applicant’s personal and financial information validation using Amazon Textract to perform OCR and extract valuable information which are store in AWS DynamoDB. Second, we perform an automated form and data validation using UiPath Robotic Process Automation bot.

Process Overview

The following architecture demonstrate step by step workflow of the process and the interaction between Textract and UiPath for the loan application process automation.

1. Client accesses the financial institution loan application website, complete the form by providing personal information and upload required documents such diver license, social security card, W2 forms and 1040 tax return and submit the form.
2. System stores the form data in database and upload documents into AWS S3 bucket after validation and scanning for vulnerabilities.
3. UiPath Orchestrator starts the process workflow and download documents from S3 bucket and invokes Amazon Textract service to analyze documents and extra key value pairs data which are stored in database.
4. Documents are scanned for vulnerabilities and uploaded to AWS S3 bucket.
5. A business process is invoked to run business rules after retrieving data from database. That includes form data and document information matching, credit validation and internal financial rules for decision making
6. Approval or rejection decision is generated from previous step and a notification email is sent out.
7. If the loan is approved, an email is sent to the applicant with next steps.
8. If the loan is rejected, the email is sent to the loan officer for review and follow-ups.
9. If the loan is approved, loan documents are generated from the document management system and users and financial information are recorded in the financial institution databases.

🔒 Krai Solutions Machine Learning and Deep Learning Initiatives

Much of health data today is in free-form medical text like doctors’ notes, clinical trial reports, and patient health records. Manually extracting the data is a time-consuming process, while automated rule-based attempts to extract the data do not capture the full story as they fail to take context into account. As a result, the data remains unusable in large-scale analytics needed to advance the healthcare and life sciences industry and improve patient outcomes and create efficiencies.

At Krai Solutions, we have built a Machine Learning Cloud based platform with is deployed either a SaaS or subscription web-based model to allow with a simple API call to quickly and accurately extract information such as medical conditions, medications, dosages, tests, treatments and procedures, and protected health information while retaining the context of the information. The platform is built on top of AWS Amazon Comprehend and can identify the relationships among the extracted information to help you build applications for use cases like population health analytics, clinical trial management, pharmacovigilance, and summarization. You can also link the extracted information to medical ontologies such as ICD10-CM or RxNorm to help you build applications for use cases like revenue cycle management (medical coding), claim validation and processing, and electronic health record creation.

Benefit of the platform:

Understand and identifies complex medical information quickly and more accurately. For example you can extract "methicillin-resistant Staphylococcus aureus" and provide context, such as whether a patient has tested positive or negative to a medical procedure. Provide several capabilities to help healthcare providers stay compliant and protect patient data by implement data privacy and security solutions by extracting and then identifying relevant patient identifiers as described in HIPAA’s Safe Harbor method of de-identification.

Use cases:

1. Perform medical cohort analysis: In oncology, it is critical that the right selection criteria are quickly discovered to recruit patients for clinical trials. Our platform understands and identifies complex medical information found in unstructured text to help make indexing and searching easier. You can use these insights to identify recruit patients to the appropriate clinical trial in a fraction of the time and cost from manual selection processes.

2. Support clinical decisions: The platform extracts medical information from patient data stored in Amazon S3 and returns structured results that you can integrate into a healthcare dashboard a care support team can access. The dashboard may contain built in early warning system to help identify individuals at risk of multiple sclerosis by extracting diagnosis, sign, and symptoms from more than 100,000 clinical notes Improve medical coding in revenue cycle management: For a hospital, the process of finding the right diagnosis in the patient notes that should be mapped to the correct code in the International Classification of Diseases (ICD) can be time-consuming and tedious. It is particularly challenging to extract diagnoses that can be represented in different ways. For example, “atrial fibrillation” is sometimes written as “AF.” With a call to our platform API, you can accurately identify abbreviations, misspellings, and typos in medical text. This reduces the time a medical coder must spend analyzing unstructured notes, decreases the time burden on clinical staff, and improves efficiency.

We have implemented a solution using AWS Serverless architecture composed of Cognito, S3, EC2, Lambda, Textract and DynamoDB described below:

To learn more, please click here Krai Solutions AI

🔒 Code Creator LLC

As Amazon Webservices expert partner: Code Creator LLC is a software provider for Amazon Web Services and AWS Marketplace. They create cloud applications, compiled, and configured in an instant, ready to run state for users and developers. Code Creator builds large portions of the software toolbox and makes it available to anyone and everyone who might find it useful, helping firms of all sizes reach a new level of productivity, whether they've invested heavily in their IT department or not. In this project the Code Creator was looking for an OCR solution that is deployed in AWS Cloud as SaaS solution using AWS Textreact. Amazon Textract is a service that automatically extracts text and data from scanned documents. We have implemented a solution using AWS Serverless architecture composed of Cognito, S3, EC2, Lambda, Textract and Elasticsearch as described below:

Overall, our client was impressed with the design approach and the deliveries I produced and open to the idea of future collaboration and support from me. After the client received our first design proposal here is the initial response and I quote “I think you are the only one of all the submitted proposals who gets it.” It was a pleasure to work with this client and we are looking forward to continuing to deliver best in class solutions to clients on AWS IQ.

🔒 National Institute of Health, NIH

As a Subcontractor for Metro Star Systems:

• Architect e-GOS Amazon Cloud Infrastructure and Systems Setup and Configuration using Cloud Formation Templates. System is Fed Ramp compatible.
• Perform database administration duties for the e-GOS application, including but not limited to capacity planning, installation, configuration, database design, data migration, performance monitoring, security, troubleshooting, and backup and data recovery tasks.
• Perform basic system administration duties, including but not limited to: installing, supporting, and maintaining e-GOS servers and planning for and responding to service outages and other problems.
• Work with subject matter experts to analyze the e-GOS code base in conjunction with database, infrastructure, and development environments to assess performance, stability and security. This includes:
• Work with subject matter experts to implement database and system improvements.

Metrics: Platform is composed of 5 environments (DEVELOMENT, QA, UAT, DEMO, PRODUCTION) AND 4 tiers: front end using Angular JS, back end using Spring-Hibernate, Data layer using MS SQL and integration tier with Apache SOLR. Production and UAT environments are composed of a cluster or servers which are site behind AWS Elastic Load Balancers (ELB) and auto managed with auto scaling groups. The database is composed of about 240 tables, 470 triggers and about 5,000,000 data rows.

🔒 Schneider Electric, APC.com eCommerce re-platform

As Senior consulting of McFadyen Solutions, provided services to design and develop a worldwide (multi language and multi currencies) Ecommerce application enabling effective customer experience and streamlining business processes. The application is built on top of Oracle Commerce Platform with some customization thereby increasing Revenue, Conversion rates, Average order value, and Traffic. The system integrates with a content management system to enable eCommerce application site content to be managed by Tridion, SDL Content Management System (CMS) and streamline business processes thereby building a foundation for more Schneider Business Units to integrate and share content seamlessly. The architecture is a multi-layers, multi-tiers system offering the benefits of performance improvement, scalability, extensibility, maintainability, and manageability.

Metrics: Schneider Electric, APC.com eCommerce platform is a multi-site multi-language eCommerce solution covering 173 languages. Each site has its own catalog that is derived from a master catalog where each language maintains its copy contents of the catalog data in a separated repository providing the content localization which includes translation and currency conversion. Because of country specific tax policies, the platform needs to integrate with multiple tax services and payment gateways.

🔒 Teleflora, eCommerce re-platform

As Senior consulting of McFadyen Solutions, designed and implemented a federated multi site eCommerce application using Oracle Commerce Platform. The design and implementation used industry best practices and standards and provided effective customer experience and streamlining of business processes thereby increasing Revenue, Conversion rates, Average order value, and Traffic.

The architecture is a multi-layers, multi-tiers system offering the benefits of performance improvement, scalability, extensibility, maintainability, and manageability.

Metrics: The architecture is a multi-layer, multi-tiers system offering the benefits of performance improvement, scalability, extensibility, maintainability, and manageability. The application platform is a multi-site eCommerce solution with about 15,000 sites. The master catalog has about 4,000 SKU. Each site has its own catalog that is derived from a master catalog where each site can override any property of category, sub-category, product, or SKU. This can bring the number of SKU to be close to 10-60 million. Teleflora e-commerce solution is a billion dollars business with about a million users.