Precision Auditing: Methodologies for Expert-in-the-Loop Verification of Retrieval-Augmented Generation (RAG) Systems

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…

What the OpenAI-Hugging Face Breach Reveals About AI Governance Failures

By Holt Hackney A series of recent AI security lapses, including the OpenAI-Hugging Face incident, is raising a broader governance question: Can technology companies adequately oversee the increasingly powerful AI systems they develop, or will […]

Colorado OIT Names Casey Cook as Principal Director of Enterprise Architecture

The Colorado Governor’s Office of Information Technology has appointed Casey Cook as principal director of enterprise architecture, a newly created leadership position focused on enterprise technology standards, governance and modernization. Cook…

The Resolution Boundary Problem: The Missing Link Between AI Governance and Real World Execution

By Ashokkumar Ganesan, AI Governance & Decision Architecture Executive Summary Enterprises today are investing heavily in AI governance: policies, principles, committees, risk frameworks, and compliance programs. Yet AI systems continue to fail in …

Designing and Developing a Scalable Small Language Model (SLM) on Microsoft Azure

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…

Large Language Models Are Still Getting Stronger, but Researchers Face New Bottlenecks in Data, Evaluation, and Safety

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 […]

The Resilience Paradox – Why Autonomous Operations Require a New Approach to Governance

By Christian Siegers, Principal, KPMG Advisory, Technology, AI & Data In conversations with platform teams, architects and operational leaders, I increasingly notice that the discussion is no longer about observability itself. Most organizations al…

Key Considerations When Allowing a Vendor to Train Its AI Models on Customer Data

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 […]

An AI-Driven Lakehouse Architecture for Scalable Healthcare Analytics, Reporting, and Machine Learning

By Vinodh Padmanaban Introduction The modern healthcare ecosystem is increasingly dependent on data-driven decision-making, requiring architectures that can seamlessly handle massive data volumes, enforce strict regulatory compliance, and support evolv…