Google Cloud Platform commitments, Committed Use Discounts, BigQuery flat-rate and edition pricing, Vertex AI and Gemini, Google Workspace, and the Apigee, Looker and Mandiant additions. Google Cloud rewards the buyer who maps consumption to the right discount instrument. Our practice exists to map it correctly.
Google Cloud's commercial model rewards buyers who understand the discount stack: Committed Use Discounts (resource-based and spend-based), Sustained Use Discounts, BigQuery editions and slot reservations, custom rate cards inside a Master Service Agreement, and the Google Workspace seat licensing that often sits alongside. The buyer who treats each as a separate negotiation overpays. The buyer who designs them together unlocks materially better economics.
Our Google Cloud practice exists to design that stack — CUD shape, BigQuery edition mix, Vertex AI and Gemini commit, Workspace seat economics — and to keep the multi-year commitment from quietly removing the buyer's ability to move workloads later.
We are not a Google Cloud partner. We do not staff your cloud team. We do not take referral fees from Google or any ISV in the Google Cloud Marketplace. We sit on the buyer side of the table and nothing else.
8 to 12 weeks. Consumption baseline, CUD portfolio design, BigQuery edition mix and the MSA counter-proposal.
4 to 8 weeks. Slot reservation modelling, autoscaling design and the on-demand vs. capacity economic break-even.
4 to 6 weeks. Tier review, AI add-on scoping and the Microsoft 365 alternative used as deliberate leverage.
Most Google Cloud engagements are fixed-fee. Larger MSA renewals are sometimes structured success-based against a documented baseline. See engagement models →
We reconcile your GCP bill across services, projects and regions; we map consumption against existing CUDs and BigQuery reservations; and we identify which workloads drive the next commit shape.
We model demand across compute, BigQuery, Vertex AI, networking and Workspace seats. We separate organic growth from project-driven peaks and run sensitivity on the CUD and slot portfolio.
We sequence the MSA renewal, any BigQuery edition transition and the Vertex AI conversation. We use Google fiscal-year discipline and the AWS/Azure alternative deliberately.
We draft the counter-proposal, redline the MSA and order forms and pre-empt the standard Google playbook — over-sized commit, restrictive CUD breakage, and Gemini provisioned-throughput lock-in.
We lead or co-lead alongside your procurement, FinOps and engineering team. We engage Google strategic accounts and field teams directly and hold the line on the clauses that matter.
We hand over a clean Google Cloud file: signed MSA, CUD portfolio, BigQuery slot reservations, Workspace seat baseline, Vertex commercial terms and the renewal calendar for the next cycle.
"They rebuilt our BigQuery slot reservation and CUD portfolio together. Same workload, 38% lower cost, and the MSA renewal still landed below the original Google proposal."
Tell us the MSA renewal date, the committed spend and any BigQuery or Vertex AI conversation in flight. We will respond within one business day with the Google Cloud practice lead.