Observability

AI Observability in 2025: How to Monitor, Evaluate, and Improve AI Agents in Production

AI Observability in 2025: How to Monitor, Evaluate, and Improve AI Agents in Production

TL;DR AI observability in 2025 goes beyond logs and dashboards — it requires tracing every agent step, evaluating quality online and offline, routing edge cases to humans, and alerting on user-impacting failures. The 5 required pillars are: Traces, Evaluations, Human Review, Alerts, and a Data Engine. Platforms like Maxim AI

LLM Observability: Best Practices for 2025

LLM Observability: Best Practices for 2025

TL;DR LLMs require a new observability stack because prompts, completions, and tool calls must be monitored together. Distributed tracing, token accounting, automated evals, and human feedback loops are now baseline requirements in 2025. Key observability gaps include prompt-completion linkage, multi-agent workflows, and black-box model reasoning. This guide outlines 7

Top 5 LLM Observability Platforms for 2025: Comprehensive Comparison and Guide

Top 5 LLM Observability Platforms for 2025: Comprehensive Comparison and Guide

TL;DR We compare the top 5 LLM observability platforms of 2025, including Maxim AI, LangSmith, Arize AI, Langfuse, and Braintrust. Each platform is evaluated across five key dimensions: tracing, evaluation, integrations, security, and scalability. The comparison outlines their strengths, features, and trade-offs to help you choose the right observability

Agent Observability: The Definitive Guide to Monitoring, Evaluating, and Perfecting Production-Grade AI Agents

Agent Observability: The Definitive Guide to Monitoring, Evaluating, and Perfecting Production-Grade AI Agents

TL;DR: Agent observability goes far beyond traditional logging or APM. It gives teams full visibility into AI agents by capturing traces, metrics, prompts, tool calls, model outputs, evaluator scores, and human feedback in real time – so you can debug failure modes, monitor quality, prevent drift, and continuously improve agents

Top 5 Tools to Monitor AI Agents in 2025

Top 5 Tools to Monitor AI Agents in 2025

TL;DR: The rapid evolution of AI agents (from simple chatbots to complex, multi-agent systems) has transformed how organizations automate workflows and deliver intelligent services. However, as AI agents become more autonomous and embedded in critical business processes, robust monitoring and observability are essential to ensure reliability, compliance, and continuous

The State of AI Hallucinations in 2025: Challenges, Solutions, and the Maxim AI Advantage

The State of AI Hallucinations in 2025: Challenges, Solutions, and the Maxim AI Advantage

Introduction Artificial Intelligence (AI) has rapidly evolved over the past few years, with Large Language Models (LLMs) and AI agents now powering mission-critical applications across industries. Yet, as adoption accelerates, one persistent challenge continues to undermine trust and reliability: AI hallucinations. In 2025, hallucinations (instances where AI generates factually incorrect

Why Monitoring AI Models Is the Key to Reliable and Responsible AI in 2025

Why Monitoring AI Models Is the Key to Reliable and Responsible AI in 2025

Introduction In the last decade, the AI industry has undergone a transformation that would have seemed improbable just a few years ago. In 2025, AI models (particularly large language models and agentic systems) are not only powering digital assistants and customer support, but are also helping make decisions in healthcare,