On this page
01
Why Vertex context matters
Gemini and Vertex AI spend usually sits close to GCP workloads, projects, and teams. Cloptima connects that model usage to the same cloud ownership context as your GCP and Kubernetes cost.
02
Call Gemini through the same governed endpoint
Connect your Vertex AI / Gemini credentials once via BYOK. Apps then call the same OpenAI- or Anthropic-compatible endpoint and just set the model — the gateway routes by model and policy, so no provider keys live in app code.
python
from openai import OpenAI
client = OpenAI(base_url="https://api.cloptima.ai/v1/ai", api_key="clop_vk_dPXO67p…")
resp = client.chat.completions.create(
model="gemini-3.8-flash", # approved Gemini/Vertex model (Cloptima maps to the provider id)
messages=[{"role": "user", "content": "..."}],
extra_headers={"x-cloptima-team": "data", "x-cloptima-app": "insights", "x-cloptima-environment": "production"},
)03
Attribute alongside GCP cost
Attach team, app, customer, workflow, and run metadata so Gemini and Vertex spend can be compared directly with GCP and Kubernetes cost centers.
04
Govern and report
Set model allowlists, environment limits, and budgets for Gemini usage, and keep attributed records to report spend across teams and apps.