.1TechnologyNovember 10, 2026 Karina Less Context, Better Answers: How Minimum Complete Context Cuts Enterprise AI CostsMost enterprise AI sends the model every connected data source, and the team pays in token costs, slow answers and wrong answers that no one can trace. Minimum complete context sends only what each task needs: 100 to 1,000 times less context. Here is how Iris.ai builds it in four steps, and what changes when the model reads less.
.2TechnologySeptember 29, 2026 Karina What Is AI Harnessing? A Definition for Enterprise AIMost enterprise AI pilots stall at expert review, when a specialist asks where an answer came from and nobody can say. AI harnessing is the discipline of controlling what an AI system is given and verifying what it produces. Learn what it is, how it differs from RAG, and the five questions every harnessed system can answer.
.3TechnologyAugust 18, 2026 Karina The Knowledge Layer Multi-Agent Systems Actually NeedEnterprises are building multi-agent systems backwards. All the investment goes into how agents communicate, almost none into what they reason on. Orchestration coordinates the workflow, but over ungoverned data it just helps agents pass flawed assumptions to each other faster. The fix is a shared knowledge layer
.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.
.5TechnologyMay 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.