Organizations now have more options to build effective RAG systems, and those options come with confusion. Many organizations are looking to capitalize on new innovations such as long context windows, knowledge graphs, reasoning models, multi agent systems, and beyond. Attend this session to learn about seven challenges with RAG systems, their associated architectural choices, and best practices to improve their performance.

GenAI solutions include several choices and trade-offs. A critical decision is: should you build custom AI solutions in-house or buy off-the-shelf products? This session brings together a debate on the trade-offs, risk and rewards of each approach. The session will be based on scenarios and use-cases to highlight key considerations such as cost, reliability , flexibility and speed for different decisions such as LLMs vs. SLMs, RAG vs. AI agents, packaged platform capability vs. bespoke custom solution, packaged vs. open-source.

Analytics and BI platforms and data Science and machine learning platforms are important technologies that drive insight-driven decision making and allow AI systems to be built and operationalized throughout the enterprise. This session unpacks the Magic Quadrants of both markets and gives inisght on the trends that you should be aware of.