Many enterprises operate expansive call centers, employing thousands of representatives who provide support and consult with clients, often spanning various time zones and languages. However, the successful implementation of a gen AI-driven smart call center analysis applications presents unique challenges such as data privacy controls, potential biases, AI hallucinations, language translation and more.

Nuclio is a high-performance serverless framework focused on data, I/O, and compute intensive workloads. It is well integrated with popular data science tools, such as Jupyter and Kubeflow; supports a variety of data and streaming sources; and supports execution over CPUs and GPUs. The Nuclio project began in 2017 and is constantly and rapidly evolving; many start-ups and enterprises are now using Nuclio in production. In this video, Tomer takes you through a quick demo of Nuclio, triggering functions both from the UI and the CLI.

Generative AI has sparked the imagination with the explosion of tools like ChatGPT, CodePilot and others, highlighting the importance of LLMs as the basis for modern AI applications. However, implementing GenAI in the enterprise is challenging, and it becomes even more difficult for banks, insurance companies, and other financial services companies. Many Financial Service companies are struggling and end up missing out on the great value of GenAI and the competitive edge it can provide.