What you’d need to build
| Capability | Lava AI Gateway | Lava Post-Request | Build It Yourself |
|---|---|---|---|
| Cost tracking | Automatic | You forward responses | You build |
| Usage metering | Automatic | You forward responses | You build |
| Pricing configuration (fixed, %, tiered) | Included | Included | You build |
| Subscription & plan management | Included | Included | You build |
| Credit & wallet system | Included | Included | You build |
| Overages | Included | Included | You build |
| Auto top-ups | Included | Included | You build |
| Usage alerts | Included | Included | You build |
| Hosted checkout flow | Included | Included | You build |
| Payment processing (Stripe) | Included | Included | You build |
| Front-end components (balances, plans) | Lava SDKs & APIs | Lava SDKs & APIs | You build |
| Enforce usage limits (pre-request) | Automatic | Check via Lava SDK | You build |
| Revenue dashboard | Included | Included | You build |
| Per-customer usage analytics | Included | Included | You build |
| Margin visibility | Included | Included | You build |
The hidden costs of building it yourself
Metering is harder than it looks
Every AI provider returns usage data differently. OpenAI gives youprompt_tokens and completion_tokens. Anthropic gives you input_tokens and output_tokens. Google uses promptTokenCount and candidatesTokenCount. Voice providers bill by the second. Image providers bill per generation.
You’d need to write and maintain parsers for every provider you use, handle streaming responses where token counts arrive at the end, and normalize everything into a single billing unit. Lava does this across 30+ providers automatically.