Noveum.ai Blog

This guide explains how enterprise teams can evaluate Voice AI systems effectively. It covers what to measure, how to measure, how to ensure your voice AI works reliably in real-world use and how to continuously improve Voice AI agents/systems.

Learn how Eval-Driven Development (EDD) transforms AI agent development. Discover frameworks, best practices, and tools for building production-ready agents with continuous evaluation.

Learn why AI agents hallucinate, the real costs of ignoring this problem, and how to automatically detect and prevent hallucinations in production using advanced evaluation scorers and root cause analysis.

Learn how to effectively monitor AI agents in production with comprehensive tracing, multi-dimensional evaluation, and automated root cause analysis. Discover why traditional APM tools fall short and how modern AI-native platforms solve the unique challenges of agent monitoring.

Experiments comparing student personas against traditional expert framing on MMLU show that student prompts deliver higher accuracy with shorter, more efficient responses.

Learn what evals for AI agents are, why they are essential for production AI, and how Noveum.ai makes running evaluations practical without slowing down your development roadmap.

MMLU benchmark comparison of GPT-OSS (thinking modes), GPT-5, O3, and GPT-4o-mini focusing on accuracy, runtime efficiency, and practical model selection.

We compared Azure o1-mini vs gpt-4o-mini on 1,000 MMLU math samples using NovaEval. Here’s how we tested, what worked, what didn’t, and when the 15× cost premium makes sense.

Discover how Noveum.ai provides comprehensive tracing and observability for AI applications, from development debugging to production optimization.

Discover how Noveum.ai provides comprehensive tracing and observability for LLM applications, RAG systems, and multi-agent workflows with our powerful Python and TypeScript SDKs.