Digital Convergence Technologies
- AI in Insurance
AI-Driven Data Processing for Real Estate Documentation
Services: AI-Driven Data Labeling and Classification
Challenge
Curve Health was operating on multiple cloud platforms, struggling with fragmented infrastructure. This created challenges around HIPAA compliance, security, scalability, and migration readiness. They needed to consolidate onto AWS to streamline operations, enhance security, and optimize their cloud environment for better performance.
Client Overview
A leader in transforming unstructured data into actionable insights, this company uses advanced AI models to process significant volumes of real estate documents, enhancing data accessibility and accuracy for the insurance sector.
Challenge
The client faced challenges in efficiently processing high volumes of complex, unstructured real estate documents, requiring automation to replace slow, error-prone manual data entry processes.
Solution
Developed an intelligent intake solution leveraging:
- Advanced AI Models: Utilized transfer learning to enable rapid customization of machine learning models for specific data labeling and extraction tasks.
- Cloud-Native Microservices Architecture: Implemented to ensure scalability and continuous optimization of processing capabilities, allowing handling of up to 40 million documents annually.
- AI-Assisted Labeling: Streamlined the extraction and classification of data from unstructured documents, significantly enhancing speed and accuracy.
Impact
- Increased Efficiency: Markedly faster data processing times with reduced manual intervention.
- Enhanced Accuracy: Improved accuracy in data extraction, reducing errors associated with manual data entry.
- Scalability: Achieved the ability to scale operations to meet high processing demands without additional resource expenditure.
Technologies Used
Proprietary AI algorithms, cloud-native services, transfer learning techniques.
