Reducing GenAI Cost: 5 Strategies
Reduce GenAI costs with five proven strategies, from agentic architectures to advanced retrieval. Optimize performance, scale efficiently, and maximize AI value.
Generative AI & LLMOps
Cost Optimization
AI Evaluation: A Framework for Testing AI Systems
Understand the Frameworks Behind Reliable and Responsible AI System Testing
Traditional software testing doesn’t work for AI. As AI becomes embedded in enterprise applications, organizations are realizing that legacy testing methods fall short. From non-deterministic outputs to AI agents, AI systems require a new playbook.
This whitepaper discusses a comprehensive framework to help you test AI systems effectively.
In this whitepaper, you'll learn about:
- The unique testing challenges posed by ML models, generative systems, and AI agents.
- Testing methods for generative content, AI planning, failure scenarios, and real-time production monitoring.
- How to monitor performance, manage bias, and apply programmatic evaluation techniques.
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