AI Architecture Review (RAG / Graph / Agents)

Many LLM systems fail because of incorrect architectural decisions, not weak prompts.

This session helps you validate or redesign your LLM / GenAI architecture based on:

1. Use case complexity
2. Data structure
3. Scale & cost constraints
4. Accuracy & trust requirements

What we’ll cover:

1. Your use case & constraints
2. When RAG is enough (and when it’s not)
3. When Knowledge Graphs make sense
4. When Agents add value vs complexity
5. Trade-offs: latency, cost, maintenance, accuracy

What you’ll leave with:

1. A validated architecture direction
2. Clear do’s & don’ts
3. Reduced risk of rework later