Insights Topic
Published INVISOM articles connected to inference economics.
7 articles
All insightsEnterprise AIFramework
An annual AI plan that names models, vendors and unit prices is out of date before its first quarterly review. Commit to the capabilities that last, hold the fast-moving choices as options, and write down what would make you change course.
Knowledge IntelligenceComparison
At the frontier, the best model changes with the month, the referee and the effort setting. Price and deployment route differ by orders of magnitude. Choose the route and build the evaluation capability; treat the model as a replaceable part.
Enterprise AIFramework
Token prices are the most visible line in a generative AI budget and rarely the decisive one. Production cost is set by architecture, by the people around the model and, if you self-host, by utilization.
Knowledge IntelligenceComparison
Regional models win on dialect, control and cost per Arabic document, not by default. Public leaderboards mostly test exam-style standard Arabic, so the choice belongs to an evaluation set built from your own users.
Cloud and PlatformsTechnical Deep Dive
Kubernetes has become the default substrate for AI inference, but it is an operating model, not a product. Adopt it when you can staff a platform team and have enough workloads to share it; otherwise, buy the managed service and keep your containers portable.
Cloud and PlatformsExecutive Guide
Most enterprises do not need to chase GPUs or the best model across clouds. They need to run AI where their governed data already lives, decide deliberately how much residency they will pay for, and keep the exit cheap.
Knowledge IntelligenceComparison
Retrieval owns facts. Tuning owns behaviour. Almost nobody should train their own model. And in 2026 the market itself has started making the decision for you.