Artificial Intelligence
RHITL: Why the Right Human in the Loop Actually Matters
Blog Commentary Look, everyone’s talking about “human in the loop” these days. It’s become one of those phrases that gets thrown around in every AI discussion, right up there with “ethical AI” and “guardrails.” But here’s the thing: just putting *a* human in the loop doesn’t cut it anymore. You need the *right* human in […]
The Great AI Splinter: Why Sovereign Stacks are Replacing Global Platforms
Gartner® just released a prediction (https://www.gartner.com/en/newsroom/press-releases/2026-01-29-gartner-predicts-35-percent-of-countries-will-be-locked-into-region-specific-ai-platforms-by-2027). “By 2027, 35% of countries will be locked into region-specific AI platforms using proprietary contextual data. Gartner also predicts that platform lock-in will rise from 5% to 35% by 2027.” This is not about technology preference. This is about sovereignty, control, and the end of the global AI model. […]
Building Secure GenAI Ecosystem: The 10 Failure Modes Behind Most Incidents (Part 2)
Enterprise GenAI Security, Explained in Two Parts As enterprises move from isolated GenAI pilots to full-scale production rollouts, the risk profile shifts—fast. In Part 1, we focused on the “front door” risks that show up early in LLM deployments: prompt injection, sensitive data exposure, supply chain weaknesses, poisoning, and unsafe output handling. But once LLMs […]
Building Secure GenAI Ecosystem: The 10 Failure Modes Behind Most Incidents (Part 1)
Enterprise GenAI Security, Explained in Two Parts As enterprises increasingly integrate large language models (LLMs) into core operations—from customer service chatbots to internal decision-making tools—the risks have evolved. A single prompt can steer behavior, retrieval can pull the wrong data, and an answer can become an action—meaning the boundary between “text” and “system behavior” is […]
Better AI with Less Data: How Domain-Specific Data Can Outperform Large Datasets
Only 15% of all AI projects succeed in production, while surveys show that the average ROI of AI implementations within the enterprise is a meagre 1.3%[1]. While these stats are as sobering as they get, they beg the question of why so many organizations continue to pour resources–money, work hours, and compute—into data collection and […]
The Solix SMART Framework for a Future-ready Data Architecture
Across industries, companies are making significant investments to turn data into strategic assets, and interest in AI is at its peak in the current market environment. However, many now face significant workflow bottlenecks due to fragmented systems, rising data management costs, and changing compliance requirements. A truly modern data architecture provides a unified, secure, and […]