Insights Topic
Published INVISOM articles connected to finops.
7 articles
All insightsEnterprise 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.
Cloud and PlatformsFramework
Vendor neutrality does not mean avoiding vendors or running everything on two clouds. It means pricing the exit before you sign, and scoring it alongside features, cost and contract terms.
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.
Data ArchitectureTechnical Deep Dive
Databricks' real strength is that pipelines, models, agents and their traces share one governance layer. The price is that its newest AI features are serverless, billed on separate lines and unevenly available by region. Adopt it workload by workload, not wholesale.
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.
Cloud and PlatformsComparison
Symmetric multi-cloud is the most expensive way to reduce cloud risk, and regulators do not require it. For most enterprises the stronger posture is deliberate concentration on one primary cloud, with a tested exit and multi-cloud only where a workload earns it.
Enterprise AIFramework
Most AI value claims are not wrong so much as unproven. The fix is to design the measurement before the build: a baseline, a credible comparison group and metrics finance has already agreed to accept.