Solvicus
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Comparison

Solvicus vs Google Cloud's CUD recommender

Google Cloud already ships committed use discount recommendations, for free, inside Cloud Billing. Any honest comparison has to start there — so this page is explicit about what Google's tooling does well, and narrow about where Solvicus is actually different.

What Google's built-in tooling does

The CUD recommender and FinOps Hub analyze your usage history — the previous 30 days by default — and recommend commitments to purchase. They cover a broader set of commitment types than Solvicus does: resource-based CUDs plus spend-based and flexible commitments across services like Cloud SQL, Spanner, AlloyDB and Memorystore. They read your billing data automatically, so there's nothing to assemble. Nothing is purchased without you — you complete the purchase in the console.

They also include genuine scenario modeling: you can toggle 1- versus 3-year terms, adjust the coverage threshold, and change or exclude the usage period, and the recommendation recalculates. If you've read elsewhere that Google's recommender is a take-it-or-leave-it number, that's out of date. And it's free.

Where Solvicus is different

The difference isn't “we have what-if and they don't.” It's the direction the model looks, and how deep the editing goes.

At a glance

 SolvicusGoogle Cloud (built-in)
What it optimizes forDemand you already know — signed contracts, a funded migration, a steady baseline — supplied as a forward planYour usage history (analyzed over the previous 30 days by default), extrapolated forward
Commitment typesResource-based CUDs (vCPU + RAM), 1- and 3-year, any machine family and regionBroader — both resource-based CUDs and spend-based / flexible commitments (Cloud SQL, Spanner, AlloyDB, Memorystore and more)
Gets your usage dataYou (or your AI assistant) provide demand and pricing — no access to your accountAutomatically, from your Cloud Billing data
Buys anything?No — recommends and evaluates only; you make every purchaseNo — recommends only; you complete the purchase in the console
What-if / scenariosEdit any individual commitment (start month, term, amount), stress-test against different demand, and see cost, coverage and utilization re-score liveYes — scenario modeling with parameter controls: toggle 1- vs 3-year terms, adjust the coverage threshold, change or exclude the usage period
Where you workIn your AI assistant (Claude, ChatGPT, Antigravity) over MCPIn the Google Cloud console
MethodA mixed-integer program solved to optimality for the inputs you give it, with the reasoning shownGoogle's own recommendation engine over your billing and usage metrics
PriceFree to start; paid plans to be announcedFree — included with Cloud Billing

When Google's free tool is the right answer

Often. If your workloads are steady and your history is a fair picture of your future, if you want commitment recommendations with zero setup, or if you need coverage for flexible and spend-based commitments that Solvicus doesn't model yet — use the built-in recommender. It's free, it's authoritative about your own billing data, and it will get you most of the way.

When Solvicus fits

When your future demand is known but not yet visible in your usage: a customer contract you've signed but not yet onboarded, a funded migration with a dated ramp, a baseline you're certain about. In those cases a history-based recommendation under-commits, and the gap is real money. It also fits when you want to interrogate and adjust the plan commitment-by-commitment before betting three years on it.

You can use both

They aren't mutually exclusive, and we'd rather say so. A common pattern: Google's recommender for what your history already justifies and for flexible-commitment coverage, Solvicus for planning the demand you know is coming. Solvicus never touches your console, so running it alongside changes nothing about your account.

Comparison based on each vendor's own public documentation, verified as of July 2026. Products change — check the vendor's current documentation before deciding. We describe what each tool does rather than ranking them: the right choice depends on how predictable your demand is and how much control you want.

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