Large language models (LLMs) have revolutionized natural language processing, enabling powerful reasoning, planning, and tool use. Enterprises are increasingly adopting LLM-powered agents to automate workflows β from meeting summarization (e.g., Microsoft Copilot) to supply chain optimization and customer service orchestration. However, deploying agentic AI systems in enterprise settings introduces unique challenges:
Designing multi-agent workflows
Planning and reasoning in dynamic business environments
Ensuring governance, security, and trustworthiness
Building evaluation datasets and improving accuracy
Keeping pace with fast-evolving frameworks (e.g., AutoGen, CrewAI)
Adapting to new models like DeepSeek-R1
This workshop brings together academia and industry to explore the design, deployment, and evaluation of LLM-driven agents tailored for enterprise use.
Weβll dive into three core themes:
Emerging Agentic Architectures & Platforms
Domain-Specific Applications
Evaluation, Governance, & Security Strategies
The ACM SIGKDD Conference on Knowledge Discovery and Data Mining is a top-tier interdisciplinary conference on data science, machine learning, and AI.
π Location: Metro Toronto Convention Centre
π Dates: August 3β7, 2025
π§ Workshop Date: Monday, August 4
π Room for this workshop: TBD