AI API cost monitoringin one dashboard.
OpenAI, Anthropic, and Gemini — unified. See which features drive spend, set budgets per label, and get alerted before you overshoot.
Multi-provider · Per-feature labels · No prompt storage
import OpenAI from 'openai';
const client = new OpenAI({
baseURL: 'https://proxy.spillr.io/v1',
defaultHeaders: {
'X-Spillr-Key': process.env.SPILLR_KEY,
'X-Spillr-Feature': 'chat',
},
});The problem
Three AI providers. Three usage pages. Zero feature context.
Each provider shows token totals for your API key — not for your product features. Spillr sits in front of all three and adds the missing layer: cost attribution by feature, with alerts and hard limits.
Siloed provider consoles
Jump between OpenAI, Anthropic, and Google dashboards to piece together total AI spend.
No feature attribution
Provider tools cannot tell you that onboarding costs 10× more than search.
Reactive cost management
Without unified monitoring, overspend is discovered at invoice time — not in real time.
Features
One spend dashboard for every AI API.
Unified multi-provider view
OpenAI, Anthropic, and Gemini costs in one place — filter by provider, model, or feature.
Feature-level attribution
Tag calls with X-Spillr-Feature. See exactly which product surface drives AI spend.
Real-time USD costs
Current model pricing applied on every call. No manual spreadsheet updates.
Cross-provider alerts
Budget thresholds and email alerts work the same regardless of which API you call.
Proxy hard stops
Block requests at the budget cap before they reach any provider.
No content logging
Monitor spend without storing prompts. Privacy by design for production apps.
FAQ
Common questions about AI API cost monitoring.
What counts as an AI API for Spillr?
Spillr monitors large language model API calls — OpenAI chat/completions, Anthropic Messages, and Google Gemini generateContent. Token usage and USD cost are logged per call.
Can I see all providers in one dashboard?
Yes. Every provider routes through Spillr with the same feature-label model. Costs aggregate by feature and split by provider in one view.
Does monitoring add latency to my API calls?
The proxy adds minimal overhead — requests pass through to the provider. Streaming responses are piped unchanged. The SDK path reports usage asynchronously after the call completes.
Can I set different budgets per feature?
Yes. Each feature label can have its own monthly or daily budget with email alerts and optional hard stops via the proxy.
Is my AI API data private?
Spillr never stores prompt text or model output. Only token counts, model identifiers, feature labels, and computed cost are retained.
Unify your AI API spend in 2 minutes.
Route each provider through Spillr. One dashboard for all your AI API costs.
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