This webinar explored the deployment of large language models on premises for analyzing a private corpus of documents, emphasizing heightened data security and privacy. 

It delved into the technical aspects, benefits, and challenges of implementing state-of-the-art language models in a local environment, taking into account the difficulties associated with developing such models when handling sensitive information that cannot be exposed to the public.

Government agencies seeking to process data in real-time have the difficult task of migrating masses of data with an added level of security to protect or safeguard mission-critical data. Agencies also operate under heavy regulatory and compliance constraints that limit who can access what data and for which purposes, adding additional levels of complexity.

During this webinar, attendees learned about:

• Unifying data by design for collaboration and a modernized data platform
• Reducing staging time and providing access to the freshest data for instant processing: resulting in better decisions and real-time analytics
• Securing data in a hybrid or distributed environment
• Effective data strategies for machine learning and artificial intelligence to analyze unstructured data at scale
• Intelligence for real-time data streams with a single source of truth and time to insights
• Streamlining data infrastructure while enhancing cybersecurity