Akshit Madan

Akshit Madan

What are Offline Evaluations and How to Set Them Up for Your AI System Using Maxim AI

What are Offline Evaluations and How to Set Them Up for Your AI System Using Maxim AI

Introduction Before deploying your AI system to production, you need confidence that it performs well across various scenarios, maintains quality standards, and produces consistent results. This is where offline evaluations become essential. Offline evaluations use curated datasets, scenario simulations, and evaluators to benchmark prompts, workflows, and agents before deployment. They
Akshit Madan
Basics of AI Observability: Sessions, Traces, and Spans

Basics of AI Observability: Sessions, Traces, and Spans

Observability in AI applications differs fundamentally from traditional application monitoring. While conventional systems deal with deterministic request-response cycles, AI applications involve multi-turn conversations, complex reasoning chains, multiple model invocations, and retrieval operations - all of which need visibility for debugging, optimization, and understanding system behavior. Maxim's observability platform
Akshit Madan