Ideas2IT Case Study

Data

Data Engineering

Education

Challenge

The Sinquefield Center for Applied Economic Research (SCAER) at St. Louis University needed a scalable, cost-effective way to manage 450TB of anonymized cell phone data for social research.

$28000

Saved in processing costs

1000+

Micro-Files Eliminated

80%

Storage cost reduction

Artificial Intelligence

Cloud

Healthcare

Challenge

Manual patient onboarding was slow and error-prone, hurting both care delivery and operational efficiency. Automation was overdue.

90%

Accuracy in Onboarding Info Extraction

Minutes

Instead of hours to onboard

App Modernization

Cloud

Healthcare

Challenge

A legacy EHR platform was buckling under performance, stability, and scale issues. The ask: a clear modernization strategy and a path to the cloud.

30%

Improved Response Time

25%

Reduced Critical Incidence

10-15%

Faster Transaction Speeds

Data Engineering

Data

Healthcare

Challenge

Scattered patient data and lack of interoperability slowed clinical decisions. The mandate: HIPAA-compliant, real-time access across systems.

15%

Reduction in Time-to-Care

47%

Faster, Informed Decision-Making

<10 Mins

To Retrieve Unified Patient Data

Cloud

Cloud Engineering

All Industries

Challenge

Skyrocketing AWS costs from dormant environments, inefficient SQS queues, and overlapping service dependencies demanded a deep infrastructure cleanup.

60%

Decrease in AWS Cost Optimization

71.3%

Decrease in AWS Cost in CGN-Sandbox Account

Impact on Uptime

Data

Artificial Intelligence

Healthcare

Challenge

80% of clinical data was unstructured, slowing diagnosis, delaying treatment, and frustrating RCM and care teams. The goal: faster, secure access to the right insights from sprawling medical records.

50%

Faster Info Retrieval for RCM + Care Teams

e-PHI

Redaction and HIPAA Compliance Built-In

30%

LLM + LangChain Powered Precision Chatbot Deployed

Case Studies

The Sinquefield Center for Applied Economic Research (SCAER) at St. Louis University needed a scalable, cost-effective way to manage 450TB of anonymized cell phone data for social research.

Manual patient onboarding was slow and error-prone, hurting both care delivery and operational efficiency. Automation was overdue.

A legacy EHR platform was buckling under performance, stability, and scale issues. The ask: a clear modernization strategy and a path to the cloud.

Scattered patient data and lack of interoperability slowed clinical decisions. The mandate: HIPAA-compliant, real-time access across systems.

Skyrocketing AWS costs from dormant environments, inefficient SQS queues, and overlapping service dependencies demanded a deep infrastructure cleanup.

80% of clinical data was unstructured, slowing diagnosis, delaying treatment, and frustrating RCM and care teams. The goal: faster, secure access to the right insights from sprawling medical records.