Improve AI Reliability with Custom Metrics [Webinar]
Blog post from Galileo
With AI becoming mission-critical, relying solely on out-of-the-box evaluation metrics is not enough. Custom metrics empower teams to define exactly what “success” means for their unique AI use cases—whether it’s domain-specific, agentic, or multimodal. In this upcoming webinar, you’ll learn how to design, implement, and validate custom metrics for AI reliability, including strategies for scaling evaluations across millions of interactions and a live demo of Galileo's proprietary small language evaluation models, Luna, which can cut the cost and latency of real-time evaluations while improving accuracy for custom metrics.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| AI Model Fine-tuning | 4 | 386 | 118 | 61 | -42% |
| Real-time | 4 | 4,075 | 1,042 | 211 | +22% |
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