From Data Depth to Agentic Heights: Unleashing AI for Business Intelligence
Webinar Speaker: Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics
Date: Wednesday, October 30, 2024
Time: 9:00 a.m. PT / 12:00 p.m. ET
Innovative business intelligence (BI) platforms are setting new standards by collecting, organizing, and deriving insights from vast, real-time analytical and transactional data. With the advent of large language models (LLMs), organizations can unlock unprecedented performance, enabling BI teams to make smarter, faster decisions.
But what if BI could go even further? Enter agentic AI—where AI agents not only process data but also engage in autonomous reasoning, providing proactive insights. This capability offers potentially immense value as well as new challenges, as businesses must understand how to leverage AI agents while ensuring their behavior remains controlled and policy-driven.
Join this webinar to hear experts from Incorta and aiXplain explain how dynamic, high-velocity data can be combined with AI agents, enabling businesses to gain deeper insights within a secure, well-governed environment. Topics include:
- What is agentic AI?
- How agentic AI can be used with transactional and operational data
- How the partnership with Incorta and aiXplain can help your organization unlock the full potential of its data
Guest Speakers
Nur Hamdan
Product Lead
aiXplain
Nur Hamdan is the product lead at aiXplain, driving AI innovations like the aiXplain AI platform and Bel Esprit. With a computer science background, her award-winning Ph.D. research in malleable user interfaces enhances her user-centric product strategies. Nur bridges UX and AI, making AI agents intuitive and accessible, advancing aiXplain’s mission to democratize AI development.
Dr. Ebrahim Alareqi
Principal Machine Learning Engineer
Incorta
Dr. Ebrahim Alareqi is a principal machine learning engineer at Incorta. Prior to his current role, he was a staff machine learning engineer at Volvo Cars R&D Tech Centre. He holds a Ph.D. in computational and data-enabled science and engineering and a master’s degree in computer science with a high-performance computing focus. He is a technical reviewer for several IEEE journals and conferences on machine learning and big data and on the planning committee for the ACM/IEEE Supercomputing Conference.
Fern Halper, Ph.D.