Put the right resources behind every team

Bring token budgets, model choices, and staffing plans together in one data-backed view — so every team has the capacity it needs to deliver.

Get the economics of AI working for you

Understand how spending, model choices, and staffing plans combine to shape cost, capacity, and delivery.

01

Recommended spend by model

02

Model choice recommendations, with projected savings and efficiency gains

03

Staffing and capacity insights across teams and projects

Tokens well spent

Know what the bill should be

AI spend grows every month, but “is that the right amount?” deserves more than a shrug. Rightsizing recommends spend by model and helps you balance committed token capacity against on-demand usage. See where you’re paying for capacity you don’t use—and where standard API rates are driving up the bill. Budget requests stop being a matter of faith.

Choose your role model

Stop paying frontier prices for routine work

When teams can’t tell which model a task requires, the most expensive option becomes the default. Rightsizing recommends the most cost-effective model for each type of work and shows the savings and efficiency gains each choice delivers, so teams choose frontier models only when their capabilities make a meaningful difference.

Talent in all the right places

Know whether every team has the capacity it needs

See where demand is outpacing team capacity, where workload and staffing are in balance, and where there’s room to take on more. Turn team capacity from a planning blind spot into something leaders can see, measure, and act on.

Budget season looks good on you

Walk into budget season with answers

Account for the full economics of AI-enabled engineering—from staffing needs to token capacity and spend. Defend the budget, justify the plan, and catch spend that isn’t producing output—before the bill does it for you.

FY27 capacity & spendEngineering + AI
OCTOBER 2026
This yearRequestedΔ
Engineering capacity
Engineering headcount8286+4
Contract capacity (FTE)9.03.5−5.5
Delivered work index1.00×1.13×+13%
AI capacity
LLM API spend / mo$24.2K$22.9K−$1.3K
Tokens / mo1.9B2.4B+26%
Capacity spend / mo$1.44M$1.36M−$80K

Bring the whole capacity equation into balance.

Connect staffing, model choice, and AI spend to the work they support — and build a budget you can defend with Spaces AI Rightsizing.