Lower AI cost
Move wasteful workloads away from premium model usage where appropriate.
Analyze model mix, identify low-risk substitutions, and estimate monthly savings.
Cost
Verified
Control
Verified
Savings
Verified
Live Workflow
Analyze model mix
Rank models by cost, token volume, provider, feature, and workload type.
Find substitution candidates
Identify workloads that may move to cheaper models with acceptable quality risk.
Estimate savings
Calculate estimated monthly savings from route changes and model substitutions.
Prioritize actions
Rank recommendations by impact, confidence, and implementation effort.
Teams often use premium models for workloads that cheaper models can handle. The optimizer turns model mix into savings opportunities.
Each page is designed to explain the product value before the backend is fully wired.
Move wasteful workloads away from premium model usage where appropriate.
Show estimated monthly savings before engineering touches routing logic.
Prioritize changes with confidence and risk labels.
A complete surface area for marketing, trials, and progressive backend integration.
The most expensive models and usage categories ranked by cost impact.
Estimate what happens when workloads move to lower-cost model routes.
Approve, reject, or schedule model optimization actions.
Short answers for buyers, operators, and early trial users.
The initial product should recommend changes first. Automated routing can come later.
By comparing current usage mix against lower-cost model alternatives and pricing assumptions.
Start now
Launch the web surface first. Connect real usage, billing, and automation in controlled batches after prospects can understand and try the product.