Aggregated enterprise architecture wisdom
By Joydeep Sarkar, of Wipro Ltd Abstract Retrieval-Augmented Generation (RAG) has emerged as the industry standard for grounding Large Language Model (LLM) outputs in proprietary data; yet, the persistence of “grounded hallucinations”, wher…
By Dr. Magesh Kasthuri Small Language Models, commonly called SLMs, are becoming a practical alternative to very large general-purpose models for enterprises that need sharper domain behavior, lower latency, better cost control, and stronger governance…
Over the past few years, progress in large language models has often been associated with a single word: bigger. Larger parameter counts. Larger training datasets. Larger computational budgets. And, with each new generation, stronger performance […]
By Chiranjib Ghatak, Senior Enterprise Architect, Wipro | Dubai, UAE Last year, a financial services team I worked with built an AI-powered document assistant for their operations staff. It worked beautifully in testing. Then they […]
By Paul Preiss, of Iasa Global Most architects treat the context view as a technical artifact. Draw the system box. Add some arrows. Label the external systems. Done. But a context view that isn’t anchored […]
By Katrina Slack and Vito Petretti Most services agreements for vendor-provided technology services contain standard provisions allowing vendors to use customer data and data generated through the provision of services to improve and enhance service […]
By Stuart Dee For much of the past decade, storing personally identifiable information within a large language model was regarded as something no responsible organisation should attempt. Early models functioned as vast statistical engines, absorbing […]
By Shelly Palmer Gartner calls agent management platforms “the most valuable real estate in AI.” The firm projects enterprises will spend $15 billion on this category by 2029, up from less than $5 million today. […]
By Eric Barroca Enterprises are falling in love with their models. A frontier LLM benchmarks well. Developers tune prompts around its response patterns. Business users grow comfortable with its outputs. Confidence builds. Workflows move into […]
By Bala Kalavala, Chief Architect & Technology Evangelist Executive Overview Across the industry, a quiet crisis is compounding. Enterprises are racing to modernize, yet the very architectural foundations meant to guide transformation are collapsin…
By Rekha Kodali The adoption of agentic AI does not fail primarily because of model limitations. It fails because enterprises attempt to operationalize autonomous behaviour without defining how agents communicate, access knowledge, and remain bounded b…
By Chris Kemp, of Kemp IT Law LLP We’ll all be familiar with sayings like: “it’s garbage in, garbage out with AI”. “It’s only as good as the data it’s trained on”. “When bad data […]