Pre-call budget control
Over-budget requests can be blocked before inference spend, with reservation commit/release behavior tested around failures and retries.
Capabilities in Action · AI FinOps & Governance
Operate AI with cost control and measurable trade-offs.
CostOps Gateway is a working v1 execution layer for AI applications. It centralizes model calls, reserves budget before provider execution, applies routing rules, handles bounded retries, records usage and supports evaluation across model configurations.
12kProjected requestsSynthetic monthly
ledger.
$672Routed estimateLocal projected USD
estimate.
$1,594Strong-only baselineSynthetic
comparison baseline.
57.8%Projected savings rateNot realized
provider billing savings.
Why this exists
The model call is easy. Operating the model call is the platform problem.
AI applications often begin by calling a model directly from product code. That works for prototypes, but teams quickly need shared controls around model selection, cost exposure, retries, evaluation and auditability.
CostOps moves those concerns into a reusable execution layer so product workflows can consume a consistent service boundary instead of reinventing them.
Core control flow
Reserve before inference. Reconcile after execution.
1Validate
Check request and routing inputs.
2Route
Select the configured fast, strong or human-review path.
3Reserve
Estimate bounded cost and reserve budget before the provider call.
4Execute
Apply timeout and bounded retry rules.
5Record
Write usage and reconcile reserved cost.
Routing policies let teams compare fast-only, strong-only and routed configurations without rewriting the product workflow.
Business-value framing
Make model choice observable before usage scales.
The included projected ledger uses a synthetic month of RunbookOps-style requests to show how route mix, incident type and model choice can change estimated cost. The purpose is not provider-billing accuracy; it is to demonstrate attribution and optimization mechanics.
Evaluation-aware cost
Compare cost alongside acceptable automated results, human-review rate, invalid-output rate and latency—not cost alone.
Evidence boundary
Projected economics are not realized savings.
- All cost fields are local estimates based on the project pricing table.
- The 12,000-request ledger is synthetic and projected.
- Local estimates do not replace provider billing records.
- The project does not include production-grade authentication or authorization.
- It does not provide a full administrative billing UI.
- Production use would require secure deployment, monitoring, incident response and larger evaluation suites.
Real application views
Make model choice, spend and routing visible.
Relevant service
Need an AI platform layer instead of another direct model call?
Use CostOps as a reference for model routing, budget controls, evaluation, retries, usage evidence and AI FinOps.