Kuldeep Paul

Kuldeep Paul

Agentic AI | LLM | Product Management | Product Marketing | Data Science | SaaS

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

AI systems have crossed the threshold from prototypes to production-critical infrastructure. Customer support bots resolve thousands of tickets. Document agents triage insurance claims. Voice agents interview candidates in real time. When these systems fail, it impacts user trust, revenue, and brand. AI observability is how you stay ahead of that

LLM Observability: Best Practices for 2025

LLM Observability: Best Practices for 2025

As large language models (LLMs) become integral to enterprise AI applications, the need for robust observability has never been more pressing. In 2025, organizations deploying LLMs must move beyond traditional monitoring tools and adopt best practices tailored to the unique challenges of generative AI. This blog explores the evolving landscape

The Best Prompt Management Tool in 2025: Why Maxim AI Leads the Way

The Best Prompt Management Tool in 2025: Why Maxim AI Leads the Way

Prompt management is now a foundational pillar in the development and deployment of advanced AI systems. As organizations scale their use of large language models (LLMs) and agentic workflows, the complexity and volume of prompt engineering have grown exponentially. In 2025, effective prompt management is not simply a technical requirement—

Choosing the Right AI Evaluation and Observability Platform: An In-Depth Comparison of Maxim AI, Arize Phoenix, Langfuse, and LangSmith

Choosing the Right AI Evaluation and Observability Platform: An In-Depth Comparison of Maxim AI, Arize Phoenix, Langfuse, and LangSmith

As AI agents become integral to modern products and workflows, engineering teams face increasing demands for reliability, quality, and scalability. Selecting the right evaluation and observability platform is crucial to ensure agents behave as intended across varied real-world scenarios. This article provides a comprehensive, technically detailed comparison of four leading

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

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

With the rapid adoption of large language models (LLMs) across industries, ensuring their reliability, performance, and safety in production environments has become paramount. LLM observability platforms are essential tools for monitoring, tracing, and debugging LLM behavior, helping organizations avoid issues such as hallucinations, cost overruns, and silent failures. This blog

How to build a Real-Time AI Interview Voice Agent with LiveKit and Maxim: A Technical Guide

How to build a Real-Time AI Interview Voice Agent with LiveKit and Maxim: A Technical Guide

AI-powered interview agents are rapidly transforming the recruitment landscape, enabling organizations to conduct scalable, consistent, and insightful candidate assessments. By leveraging real-time voice capabilities and advanced observability, these systems offer a glimpse into the future of automated interviewing. This guide presents a comprehensive walkthrough for building a robust AI Interview

What is an LLM Gateway? A Deep Dive into the Backbone of Scalable AI Applications

What is an LLM Gateway? A Deep Dive into the Backbone of Scalable AI Applications

Large Language Models (LLMs) have rapidly transformed how organizations build, deploy, and scale AI-powered applications. From intelligent chatbots to advanced document processing, LLMs are at the heart of modern automation and digital intelligence. Yet, as teams move from experimentation to production, a new set of infrastructure challenges emerges, chief among