LLM Observability: Monitoring the Performance and Behaviour of Generative AI Models

As large language models (LLMs) find their way into real-world applications—such as chatbots, code assistants, customer service, and research tools—understanding how they behave in the wild has become just as important as building them. That’s where LLM observability steps in. Unlike traditional software, LLMs are dynamic and unpredictable. A single...

OpenTurf Launches TurfAI: An Enterprise AI Studio to Simplify, Scale, and Secure Intelligent Workflows

Enterprises know they need AI to compete, but the journey to integrate it is often a maze of complexity, cost, and security concerns. That's why OpenTurf developed TurfAI—an enterprise-grade AI orchestration framework. TurfAI is a new kind of AI studio, purpose-built to simplify intelligent workflows, making it easier than ever...

Building the Future of Document Intelligence for Fexo

The Challenge Fexo approached OpenTurf with an ambitious vision: to transform how the Banking, Financial Services, and Insurance (BFSI) sector processes vast amounts of document-intensive data. Their goal was to build an enterprise-grade platform capable of converting unstructured information into actionable intelligence using advanced AI. The core challenges were substantial:...

The Role of AI Code Assistants in Boosting Developer Productivity and Code Quality
     

Modern developers aren’t just writing code—they’re collaborating with AI. If you’ve spent any time in an IDE recently, chances are you’ve encountered an AI code assistant nudging you with autocomplete suggestions, offering to refactor your logic, or generating entire functions before you finish typing the first line. What started as...

Key take‑aways from Andrej Karpathy’s keynote “Software Is Changing (Again)”

Three paradigms of software Software 1.0 – traditional hand‑written code.Software 2.0 – neural‑network “weights as code”, produced by training on data.Software 3.0 – large‑language‑model computers that you “program” with English prompts; the prompt is now the source code.  Take a look at the video here Learnings from two years of using AI tools for software engineering...

The Unseen Engine: How Performance Engineering Powers DevOps & SRE

"If software is the engine of modern business, then Performance Engineering is the meticulous tuning that ensures it runs at peak efficiency, reliably, and without falter." Why this Matters  Today’s cloud‑native, micro‑service heavy stacks ship dozens of releases a day and serve globally distributed users who abandon slow pages in...

Detect Early, Optimize Fast: Smarter Manufacturing with Data

Executive Summary Symbiotic Automation Systems (SAS), a 25+ year industrial automation leader and Siemens-authorized system integrator , identified a critical gap: its manufacturing clients collected rich process data but had no real-time analytics tools. Previously, operators exported batch data to spreadsheets for manual analysis, making it slow to spot trends,...

Gen AI & Observability trends in 2025

As digital infrastructures grow increasingly complex, traditional observability methods often fall short in providing comprehensive insights.In 2025, observability has evolved from a reactive monitoring practice to a proactive, intelligent system powered by Generative AI. This transformation is enabling organizations to detect anomalies earlier, reduce mean time to resolution (MTTR), and...

How to Choose the Right Metrics for Your A/B Tests

Choosing the right metrics for your A/B tests is crucial to unlocking actionable insights and driving meaningful improvements in your product or website. But running an A/B test is not just about splitting your audience and measuring what performs better—it's about measuring the right thing. Whether you're optimizing a fintech...