Giving Your Teams a Real AI Budget with LiteLLM

A hands-on guide to putting a gateway between your people and the model vendors, so that every call is attributed to a named person and a team, every team has a ceiling that resets on a schedule, a daily bound contains the runaway agent, and the finance team finally gets a per team breakdown. Covers deployment with Docker and Postgres, teams and keys, stacked budget windows, rate limits, model tiering, request tags for chargeback, PII guardrails, and the day two work nobody warns you about.

Nobody Knows What Your Company Spends on AI

Every company now has employees using OpenAI, Anthropic and Gemini every day, and almost none of them can say who asked what, what data left the building, or what any of it returned. This article argues that AI governance by policy fails for the same reason shadow IT policies failed, that the request for a fixed AI budget is the wrong question, and that FinOps is the practical way in: the only one of the three unknowns you can measure today is cost, and measuring it is what buys you the other two.

The Multi-Cloud Illusion for the State: Duplication Is Not Sovereignty

Multi-cloud is sold to African countries as the answer to both resilience and digital sovereignty: spread workloads across several hyperscalers and you dilute risk and vendor power. Under Togo's Law 2019-014 on personal data and the ANCY cybersecurity regime, that promise does not hold. This article argues that multi-cloud does not divide legal exposure, it multiplies it, and closes with a decision framework for when it is legitimate and when it is not.