Kuldeep Paul

Kuldeep Paul

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

RAG Debugging: Identifying Issues in Retrieval-Augmented Generation

RAG Debugging: Identifying Issues in Retrieval-Augmented Generation

Retrieval-Augmented Generation (RAG) has rapidly emerged as a cornerstone of modern AI applications, empowering systems to deliver contextually rich and accurate responses by marrying powerful language models with external, authoritative knowledge bases. Yet, as organizations increasingly deploy RAG-powered solutions for search, customer support, recommendation engines, and more, the complexity of

LLM Observability: How to Monitor Large Language Models in Production

LLM Observability: How to Monitor Large Language Models in Production

Introduction The rise of Large Language Models (LLMs) has transformed the landscape of AI-driven applications, from conversational agents to advanced search systems. As these models permeate enterprise workflows, the challenge shifts from building impressive prototypes to maintaining reliable, scalable, and high-quality production systems. LLM observability (the practice of monitoring, tracing,

Agent Tracing for Debugging Multi-Agent AI Systems

Agent Tracing for Debugging Multi-Agent AI Systems

Introduction The rapid evolution of artificial intelligence has ushered in a new era of multi-agent systems, where teams of autonomous agents collaborate to solve tasks that exceed the capabilities of single models. These systems have become pivotal in domains ranging from conversational AI and document processing to autonomous decision-making and

AI Reliability: How to Build Trustworthy AI Systems

AI Reliability: How to Build Trustworthy AI Systems

Introduction Artificial intelligence is rapidly transforming industries, driving innovation, and redefining how organizations operate. However, as AI systems become more pervasive and influential, the imperative to ensure their reliability and trustworthiness intensifies. Building trustworthy AI is not only a technical challenge, it is a multidimensional endeavor that encompasses ethics, governance,

How to Ensure Reliability of AI Applications: Strategies, Metrics, and the Maxim Advantage

How to Ensure Reliability of AI Applications: Strategies, Metrics, and the Maxim Advantage

Summarise this Blog with ChatGPT Artificial intelligence is rapidly reshaping industries, from customer support to healthcare, finance, and beyond. Yet, as organisations integrate AI into mission-critical workflows, reliability remains the defining factor that separates successful deployments from costly failures. In a world where AI agents can autonomously handle complex tasks,

Top 5 AI Evaluation Tools in 2025: In-Depth Comparison for Robust LLM & Agentic Systems

Top 5 AI Evaluation Tools in 2025: In-Depth Comparison for Robust LLM & Agentic Systems

As AI agents and large language models (LLMs) move from experimental playgrounds to powering mission-critical business workflows, the question is no longer if you need to evaluate — it’s how you’ll do it. In 2025, the landscape of AI evaluation tools has matured rapidly, offering teams not just basic

What Are AI Evals?

What Are AI Evals?

“AI evals” is one of those phrases that gets thrown around in every AI product meeting, but ask ten people what it means and you’ll get ten different answers, half of them vague, the other half suspiciously buzzwordy. Yet, if you’re building, shipping, or scaling anything with LLMs,