.1AI Across IndustriesAugust 11, 2026 Karina Adopting AI in a Regulated Enterprise: Moving Beyond the Proof of ConceptEnterprise AI has split into two camps: those running experiments and those in production. For regulated industries, crossing that gap is brutal — 62% of enterprises stay stuck in pilots. The blocker is rarely the model. It is a foundation that treats data governance as a patch instead of the structure holding everything up.
.2AI Across IndustriesAugust 4, 2026 Karina How Enterprise AI Should Actually Be Built: Context First, Model SecondMost enterprise AI starts with the model and recovers context later — which is why accuracy breaks in regulated work. The fix is to reverse the sequence: build a validated semantic layer before the LLM touches your data. See how a context-first architecture hit 97% accuracy where conventional RAG stalled at 80%.
.3AI Across IndustriesJuly 21, 2026 Karina You Do Not Control Whether Your AI Model Stays Available. Your Architecture Decides What That Costs You.Most enterprise AI stacks treat one hosted model as a hard dependency. When Anthropic suspended Fable 5 and Mythos 5 globally in June 2026, that dependency became a single point of failure overnight. Resilience is not about picking the right vendor. It is about decoupling your knowledge layer so any model is replaceable.
.4TechnologyJune 25, 2026 Karina You're Running an LLM. But Do You Actually Know If It's Working?You deployed the model. The team tuned the prompt, the architecture, the pipeline. But do you know if the output is actually good? Most enterprises operate with an evaluation blind spot, catching failures only after they reach a customer. Here is what to measure, what to fix, and where to start today.
.5AI Across IndustriesMay 12, 2026 Karina The Context Layer Market Is Here: What Enterprise Leaders Need to KnowFoundation models are commoditizing. Proprietary knowledge is becoming the differentiator. That shift is creating a new category of enterprise AI infrastructure: the context layer. Here's what's driving the market, what analysts are tracking, and the three shifts AI buyers need to make in how they evaluate their stack.