What’s the best way to set up credit burndown for my AI product?
Schematic Provides Credit-Based Billing Without Needing Custom Logic
Flexibility
Credits are flexible for customers and map well to the AI costs.
Avoid Complex Implementation
Credits require usage tracking, renewal triggers, and balance accounting.
Credits as a Service
Schematic make Credit Burndown simple to add and manage.
The Problem with Spiky Usage
Schematic makes credit burndown simple — no custom metering or billing logic required.
The Old Way
- Track usage manually in a database
- Write scripts to decrement credits
- Manually reset credits each month
- Support flooded with "why did I get blocked?" tickets
The Schematic Way
- Upload or assign credit bundles per customer
- Automatically burn down credits with usage events
- Enforce limits in real-time via feature flags
- Alert customers before they run out
Use Cases
- Token-based LLM pricing
- Pay-as-you-go APIs
- Trials with limited compute
- Prepaid usage bundles
Comparison
Capability
Stripe
Orb
Metronome
Schematic
Credit tracking
✅
✅
✅
✅
Usage-based burn down
❌
✅
✅
✅
Real-time enforcement
❌
❌
❌
✅
Usage alerts
⚠️
✅
⚠️
✅
Easy credit resets or top-ups
❌
❌
❌
✅
Support for AI-specific patterns (token, inference time, etc.)
❌
❌
❌
✅
Built for
AI Founders
Balancing infra costs with monetization
Product Managers
Managing usage-based pricing without dev bottlenecks
Engineers
Engineers who want billing to “just work” — especially at scale
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