What billing tools work for AI companies with spiky usage patterns?
Schematic is Billing Infrastructure Built for AI’s Wild Usage Patterns
Daily API Calls
One customer makes 10k API calls one day, 100 the next.
GPU Complexity Costs
GPU time costs spike with model complexity.
Infrastructure Scales
Your infrastructure scales — but your billing system can’t.
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The Problem with Spiky Usage
Schematic Handles Spiky AI Usage by Design
Use Cases
With Schematic, You Can:
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Developers
Pricing
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Stripe can’t meter fast enough to cap or alert
Billing runs behind, creating refund risk or missed revenue
Customers churn when surprises hit
Devs are stuck patching logic instead of shipping product
Capability
Stripe
Orb
Metronome
Schematic
Real-time usage metering
✅
✅
✅
✅
Credit systems to absorb spikes
⚠️
⚠️
⚠️
✅
Feature flags to enforce hard limits
❌
❌
⚠️
✅
LLM APIs: unpredictable token volumes per call
Image generation: heavy GPU usage tied to single requests
Search and embedding services: variable demand based on customer traffic
Developer platforms: usage tied to customer adoption cycles
Gate features and usage without writing code
Define usage caps, paywalls, and alerts
Ship trials, paywalls, add-ons, and plan changes in hours
Stop chasing billing bugs or misaligned invoices
Grow revenue while controlling infrastructure cost
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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Alerts and usage visibility
⚠️
✅
⚠️
✅
Hybrid plans (seat + usage)
⚠️
✅
✅
✅
Support for AI-specific patterns (token, inference time, etc.)
❌
❌
❌
✅
