All methodologies
AI Pricing valuation
Price AI features and usage-based products.
Methods
- Cost-plus and comparable pricing analysis
Data sources
- Market pricing benchmarks
Valuation guide
Price the outcome, meter the cost. AI features should be priced on customer value while usage costs set the floor you cannot cross.
Three models dominate: seats for workflow tools, usage credits for API-like consumption, outcome cuts for automation. Hybrids usually win.
Common questions
How should I price my AI feature?
Start from the cost it removes or revenue it creates, verify margin above inference cost at scale.
Per-seat or usage-based?
Seats when value scales with users, usage when value scales with volume. Most end up hybrid.
How do I keep margins as usage grows?
Cache aggressively, route simple queries to small models, bake inference cost into tiers from day one.
Live accuracy
Completed valuations: 0
Outcome tracking is live — model stats until owners record outcomes.