.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 28, 2026 Karina Sovereign AI for Regulated Industries: Keeping Control of Your Data, Models and KnowledgeOwning your compute protects where your AI runs. It does nothing to protect what your AI knows. The knowledge layer is where lock-in hides, because it is rarely built to move between vendors. Sovereign AI means decoupling that layer so the model becomes swappable and your institutional knowledge stays yours.
.4AI Across IndustriesJuly 22, 2026 Karina Welcome Iris.ai's CMO - Liana HakobyanEvery new chapter at Iris.ai starts with people who embody how we build. Today, that chapter continues with the appointment of our Chief Marketing Officer.
.5AI 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.