Pricing Advisor
Adjust credit costs as provider economics change
Provider costs change. Usage patterns shift. Margin targets move. Pricing Advisor tracks provider cost, your credit pricing, and margin targets — suggests changes when something drifts. You apply or reject. Deterministic, versioned, human-approved.
The drift
Credit costs need to adapt
You set credit costs for each AI action. But provider economics change — models get cheaper, new ones launch. Usage patterns shift. Your margin targets may evolve. Static pricing drifts. Developers need to adjust without manual guesswork or exposing cost complexity to users. Recommendations should support judgment, not replace it.
Why the old approach breaks
Set-and-forget pricing drifts
If you set credit costs once and never revisit, margins drift. Provider cost drops — you're overcharging or leaving money on the table. Provider cost rises — you're underwater. Manual tracking across spreadsheets and provider dashboards doesn't scale. And raw model cost is only one input. Product value, competitive positioning, and user willingness to pay matter. You need data to decide, not a black box.
Example
A pricing recommendation scenario
Your chat.reply event costs 4 credits. Provider cost for GPT-4o has dropped; your margin is above target. Pricing Advisor suggests a change. You apply or reject.
4 credits
3 credits
chat.reply · Provider cost down 22%, margin above target
How Chargly handles it
Recommendations, version history, apply/reject
Pricing Advisor tracks provider cost, your credit pricing, and margin targets. When something drifts, it suggests changes. Recommendations are deterministic and explainable. You apply or reject. Every change creates an immutable version. No autonomous pricing. Estimated lift visibility helps you understand impact before acting. Full audit trail.
Try it
See how inputs shape the recommendation
Pricing Advisor weighs current cost, usage trends, margin targets, and churn risk. Adjust the levers below — the recommendation updates live.
This is a simplified preview. Chargly handles the real pricing logic in production.
See how Chargly applies this in productionWhere it fits in the product
Dashboard, MCP, metering
Pricing Advisor lives in the dashboard — inspect recommendations, apply or reject. MCP tools let agents participate in the workflow (e.g. fetch recommendations). Pricing rules feed into metering; when you apply a change, the new credit cost takes effect for the next event. The system stays consistent: you control pricing, Chargly handles the mechanics.
Add pricing intelligence to your AI product
Recommendations, version history. Free to start.