Native Integration

GCP Vertex AI Integration

Unify Google Cloud Vertex AI spend in Finomics with end-to-end tokenomics tracking across foundation models, custom endpoints, GPU/TPU compute nodes, and pipeline workflows.

What Finomics tracks for GCP Vertex AI

Track Foundation Model API usage, custom model endpoints, and tuning costs on Google Cloud Vertex AI

Token consumption and API invocation costs for Gemini, PaLM, and third-party models in Model Garden

Vertex AI custom prediction endpoint costs and GPU/TPU accelerator node hours

Model training, tuning, and evaluation job compute and storage expenditures

Vertex AI Feature Store, Vector Search, and Search & Conversation usage costs

Per-project and per-service account API key metrics and prompt/response token ratios

Spend attribution by Google Cloud project, label, folder, and billing account

Why govern GCP Vertex AI with Finomics

Foundation Model Tokenomics

Track exact input, output, and multimodal token spend across Vertex Model Garden foundation models.

Endpoint & GPU Forecasting

Predict future Vertex AI endpoint compute and API consumption trends with predictive modeling.

Project Guardrails

Enforce cost limits and quota thresholds on Vertex AI custom endpoints and batch inference jobs.

Automated Label Chargeback

Map GCP labels, folders, and projects to business units for seamless showback and chargeback.

Runaway Job Detection

Alert teams instantly when unattended training jobs or endpoint traffic cause abnormal spend.

Managed vs Custom ROI

Compare costs of managed Model Garden APIs versus self-hosted custom endpoints on TPU/GPU.

Get started in minutes

Connect

Grant read-only access to your Google Cloud Billing export and Cloud Monitoring.

Sync

Finomics ingests Vertex AI token usage, endpoint metrics, and billing records.

Attribute

Map GCP projects, folders, and labels to teams, cost centers, and applications.

Govern

Set model-level budgets, endpoint idle alerts, and quota guardrails.