Build an AI application or agent whose reliability is validated against its real workload
Develop an AI system such as a customer-service chatbot, RAG application, code assistant, or tool-using agent, and evaluate both the model's quality and the production system's accuracy, latency, throughput, safety, formatting, and cost.
From IBM Technology — LLM & AI Agent Benchmarks vs Reality: Why AI Applications Break at 00:39
Problem: A model can score highly on a leaderboard yet produce incorrect answers, respond too slowly, fail under real traffic, or cost too much in production.
For: Teams building AI applications or agents for customer service, document question answering, coding, or interactions with business services.
Examples
- Customer-service chatbot: evaluate whether responses are helpful, appropriately toned, correct, and free of hallucinated company or product details.