Agentic AI will be the focus of a free webinar detailing how semiconductor manufacturers can accelerate root cause analysis across complex, siloed production data. The session highlights methods for connecting insights from metrology, tool traces, chemical analysis, and facilities systems to shorten time to resolution when yield excursions occur.
Agentic AI and cross-domain analytics
According to the organizers, semiconductor yield issues rarely originate from a single source, and critical evidence is typically dispersed across multiple systems. Growing data volumes can make traditional dashboards slow and fragmented. The webinar will outline how a purpose-built semiconductor analytics platform uses Agentic AI, domain-specific visualizations, and push-down compute to speed investigations, even when working across billions of data points.
What attendees will learn
The program includes a live demonstration of a multi-domain root cause investigation using Spotfire Industry Pro. Presenters will show how engineers can connect insights without moving data, apply semiconductor-specific visual tools, and automate complex cross-domain analyses with Agentic AI.
Key takeaways
- Why siloed manufacturing data can delay yield recovery and increase costs
- How Agentic AI can automate sophisticated analytics and visualization generation
- Approaches for scaling high-performance analytics across massive fab datasets
Who should attend
The webinar is designed for Yield, Process, and Integration Engineers, Fab and Manufacturing Operations Managers, Quality and Reliability Engineers, and data and analytics leaders supporting wafer fabs, foundries, OSATs, and IDMs who need to identify issues quickly while maintaining confidence in decisions.
Registration
Organizers encourage interested professionals to reserve a seat. The free session will cover how leading semiconductor teams are accelerating root cause investigations, scaling analytics across large datasets, and turning disconnected information into actionable manufacturing intelligence.