.1TechnologyMay 5, 2026 Karina What Is the AI Context Layer, And Why It Changes Everything About Enterprise AIEnterprises are spending more on AI than ever, yet 95% of pilots deliver zero measurable ROI. The constraint is not weak foundational models. It is a fundamental lack of proper data context. The AI context layer sits between raw enterprise data and model output, delivering organizational knowledge at the exact point of inference.
.2AI Across IndustriesApril 28, 2026 Karina How Pharma and Life Sciences Are Using AI to Accelerate Knowledge WorkPharma generates vast amounts of research data – but most of it remains unused. This creates costly inefficiencies and slows innovation. The real challenge isn’t creating knowledge, but accessing and activating it. Discover how AI, powered by the right infrastructure and context layer, turns static documents into usable intelligence.
.3AI Across IndustriesApril 21, 2026 Karina Agentic AI in the Enterprise: What It Is, What It Promises, and What It Needs to Work Agentic AI is the next leap beyond generative AI: systems that don't just answer questions, but plan, decide, and execute multi-step work autonomously. The promise is massive but most enterprises lack the data infrastructure, governance, and integration layer to make it work. Here's what agentic AI actually is, and what it takes to deploy it safely.
.4AI Across IndustriesApril 14, 2026 Karina The Hidden Cost of Knowledge Silos: What Disconnected Data Is Doing to Your TeamsEmployees waste 1.8 hours daily searching for scattered information. Multiply that across your workforce and the cost becomes undeniable. Knowledge silos don't just slow teams down – they compromise decisions, kill AI readiness, and lock your most valuable institutional knowledge out of reach.
.5AI Across IndustriesMarch 31, 2026 Karina The Data Readiness Gap: Is Your Organization Actually Prepared for Enterprise AI?99% of organizations are increasing AI investment - yet 61% admit their data isn't ready for it. The result: pilots that stall, GenAI that hallucinates, and ROI that never materializes. The problem isn't your model. It's your foundation. Discover the three signs your data isn't AI-ready, and how to close the gap.