Building Generative AI application for highly regulated industries | S02 EP37 | Lets Talk About Data

The discussion focused on the use of generative AI in highly regulated industries like healthcare and financial services. Chintan and Suresh, Senior Partner Solutions Architects at AWS, explained that highly regulated industries have strict guidelines and regulations around data security, compliance, and traceability. They highlighted key use cases for generative AI in these sectors, such as improving productivity, automating customer service, and identifying risks and anomalies. The speakers emphasized the importance of ensuring data quality, protecting sensitive information, and maintaining full auditability of all processes.

The speakers demonstrated a use case involving a loan origination application. They showed how the system uses natural language processing and large language models to extract relevant information from various documents, create a graph database to capture complex relationships, and then apply decision rules to determine loan eligibility. The system anonymizes sensitive data, stores it securely, and uses the AWS Nitro Enclave technology to perform computations in a fully isolated and attested environment. This ensures that even internal actors cannot access the raw data during processing.

The speakers highlighted the advantages of using generative AI in these applications, including the ability to remove human bias, increase efficiency, and provide full traceability of the decision-making process. They stressed the importance of carefully considering data quality and bias in the underlying models, as these can impact the accuracy and reliability of the system. The speakers also invited the audience to attend a hands-on workshop at AWS re:Invent to explore the Nitro Enclave technology in more detail.

- Highly regulated industries have strict guidelines and regulations around data security, compliance, and traceability
- Key use cases for generative AI include improving productivity, automating customer service, and identifying risks and anomalies
- Demonstrated a loan origination application that uses natural language processing and graph databases to extract and analyze information
- Leveraged AWS Nitro Enclave technology to perform computations in a fully isolated and attested environment
- Emphasized the importance of data quality and model bias to ensure accurate and reliable systems
- Invited audience to attend a hands-on workshop at AWS re:Invent to explore the Nitro Enclave technology

Ibrahim Emara, RDS Specialist Solutions Architect @ AWS

Chintan Sanghavi, Lead Architect - FinTech/FSI Partner ISVs

Suresh Veeragoni, AI Technologist @ AWS