Customer Challenges

To ensure fair play and compliance in youth sports, NSID verifies a player’s age and grade before issuing a badge of eligibility. This meant collecting birth certificates and report cards from every participant and confirming the details against league requirements. Initially, NSID relied on support agents to manually review each player’s submission (birth certificate and report card).

The existing process posed three significant challenges.

1. Lack of Scalability

If the number of players grew, manually verifying each application or hiring new agents on the fly became impractical. In short, the process was time-consuming and resource-intensive.

2. Rising Costs

Adding agents, as required, drove up expenses. Recruiting, onboarding, and continuously training staff to keep pace with growing demand was unsustainable.

3. Reduced Speed

Manual verification introduced long turnaround times—often taking hours, which delayed player onboarding and slowed down league operations.

Without intervention, NSID faced mounting operational costs, delayed user experiences, and potential reputational impact from verification errors. To overcome these challenges, NSID identified generative AI as a strategic solution to automate document validation, accelerate player verification, and ensure accuracy at scale.

Ibexlabs guided the customer through an AWS generative AI adoption strategy, foundation model selection and customization, production launch, and ensured security and compliance. 

By replacing manual document review with a generative AI-powered solution built on Amazon Bedrock, AWS Lambda, Amazon S3, Amazon GuardDuty, and Amazon Textract, Ibexlabs enabled NSID to achieve faster, more accurate, and cost-effective identity verification at scale.

Ibexlabs had been a long-term partner for NSID, offering managed AWS security and modernization services. This foundation of trust and technical expertise positioned Ibexlabs as NSID’s partner of choice.

This case study showcases Ibexlabs’ ability to design, implement, and manage secure, production-ready generative AI solutions on AWS. 

Partner Solution

1. Automated Document Intake

Today, the moment a player uploads a certificate to the system, an AWS Lambda function immediately recognizes it and begins processing the document in real time. Lambda functions scale automatically with demand, and the serverless setup ensures that there are no delays, even when hundreds of players submit documents simultaneously.

2. Secure & Scalable Storage

All player documents are uploaded and stored in Amazon S3, providing highly durable, cost-effective storage. S3 ensures that NSID can handle unlimited scalability while keeping sensitive player data secure and easily retrievable.

3. Intelligent Document Processing

Once stored, the documents are processed through Amazon Textract, which automatically extracts key information such as player names, dates of birth, and grade levels. Textract’s ability to not only scan text but also understand and extract structured data from scanned PDFs and images improved accuracy scores and sped up verification dramatically.

4. Data Validation Layer

The processed data is then validated and enriched using application logic hosted on Amazon EC2 instances behind Application Load Balancer (ALB), ensuring high availability and load distribution across multiple Availability Zones.

5. Fraud Detection 

Ibexlabs’ generative AI system goes beyond data extraction and applies intelligent fraud checks for cross-field validation and document forensics to identify anomalies, such as inconsistent fonts and manipulated images. 

6. Security Layer

Security and observability are reinforced through a multi-layered approach. AWS WAF, and AWS Security Hub provide perimeter protection and threat intelligence, while AWS Config, CloudTrail, and CloudWatch enable compliance tracking, audit logging, and proactive monitoring.

7. Seamless User Verification

After data processing, Ibexlabs’ solution automatically compares the extracted details against the information submitted by the player during registration (e.g., name, date of birth). If the particulars align, NSID issues a green badge for authenticity. 

Solution Optimality

With our solution, the client reduced verification time from hours to minutes.

The selected architecture leveraged Amazon Textract for intelligent document extraction and EC2-based application logic for validation and enrichment, integrated with RDS for structured data storage. This approach ensured full control over sensitive data, seamless scalability through AWS native services, and faster processing times without any dependence on external APIs.

Alternative approaches, such as outsourcing verification to third-party vendors or building an OCR model from scratch, were evaluated but found unsuitable due to higher costs, data privacy risks, and lack of scalability.

Faster Verifications

Previously, NSID took hours to complete a review. By automating the ingestion, extraction, and verification of birth certificate data with AWS generative AI services, NSID drastically reduced turnaround times. What previously took hours was brought down to a few minutes. 

Lower Operational Costs

By automating verification, NSID eliminated the need for large teams of support agents, cutting operational expenses. The organization can now process far more verifications at a fraction of the cost, freeing up budget for innovation and other administrative solutions for youth sports organizations. 

Built for Scalability

Built entirely on AWS-native, serverless services for generative AI processing, the architecture allowed NSID to handle thousands of verification requests without worrying about infrastructure limits or downtime. Whether it’s 100 applications or 100,000, the system scales seamlessly with demand.

Improved Fraud Detection

Unlike manual review, which relies heavily on human attention to detail, the generative AI-powered system introduced advanced fraud-detection logic. It not only reduced the risk of fraud but also ensured greater accuracy.