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Documentation Index

Fetch the complete documentation index at: https://docs.requesty.ai/llms.txt Use this file to discover all available pages before exploring further.
Requesty tracks every dollar you spend on AI — broken down by model, provider, user, API key, and time period. See exactly where your budget goes and how much you’re saving through caching and routing optimization.

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Cost Overview

The Analytics dashboard shows your spending in real-time:
  • Total Spend: Current cost for the selected time period
  • Cost Over Time: Bar chart showing daily/weekly/monthly cost trends
  • Cost by Model: See which models cost the most
  • Cost by User: Track per-user spending across your organization
  • Projected Spend: Estimated end-of-period costs based on current rate

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Cost Breakdown

Group your costs by any dimension:
Group ByWhat you see
ModelCost per model (e.g., anthropic/claude-sonnet-4-5: 420,‘openai/gpt−4.1‘:420, `openai/gpt-4.1`: 180)
ProviderTotal spend per provider (Anthropic, OpenAI, Google, etc.)
UserPer-user cost attribution
API KeyCost per API key — useful for tracking per-application spend
Custom FieldAny Request Metadata field (e.g., environment, feature)

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Savings Tracking

The Savings tab in analytics shows how much you’re saving:
  • Cost Savings ($): Total dollars saved through prompt caching
  • Cost Savings (%): Percentage saved vs. what you would have paid without caching — shown as a gauge chart
  • Cache Hit Rate: What percentage of your requests hit cache
  • Token Cache Rate: What percentage of tokens are served from cache
  • Per-Model Savings: Table showing which models benefit most from caching
Check the Savings tab regularly. If your savings percentage is below 20%, consider enabling Auto Caching for your most-used models.

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BYOK Cost Comparison

When using Bring Your Own Keys, the Cost Overview chart splits into:
  • Requesty Cost: What you pay through Requesty-managed keys
  • Provider Cost: What you pay directly to providers through your own keys
This makes it easy to compare pricing and decide when BYOK is more cost-effective.

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Budget Controls

Control spending at multiple levels:
  • Project Limits: Set monthly spend caps per project — each user’s Private project can have its own limit
  • API Key Limits: Set monthly spend caps per individual API key
  • Spending Alerts: Get notified via email or webhook when spending exceeds configurable thresholds
  • Group Budgets: Set spending limits for teams
When a spend limit is reached, new requests for that project or key are blocked until the next billing period.

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Cost Optimization Tips

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Use Cheaper Models Where Possible

Not every task needs a frontier model. Use the Advanced analytics tab to find tasks where a cheaper model would work:
  • Route simple classification tasks to openai/gpt-4o-mini instead of gpt-4.1
  • Use anthropic/claude-haiku-4-5 for summarization instead of Sonnet

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Enable Caching

Auto Caching can reduce costs by 25-90% for workloads with repeated system prompts or similar queries. Check your Savings tab to see your current cache hit rate.

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Use Routing Policies

Fallback Policies can start with cheaper models and only fall back to expensive ones when needed — automatically reducing your average cost per request.

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Track with Metadata

Tag requests with Request Metadata to understand cost by feature, environment, or customer: 
response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4-5-20250514",
    messages=[{"role": "user", "content": "Hello"}],
    extra_body={
        "requesty": {
            "metadata": {
                "feature": "chatbot",
                "environment": "production",
                "customer_id": "acme-corp"
            }
        }
    }
)
Then filter by feature, environment, or customer_id in the Advanced analytics tab to see cost breakdowns.

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Export Cost Data

From the Advanced tab, export your cost data as CSV:
  1. Set Metric to cost, Group By to model (or any dimension)
  2. Choose your time range
  3. Click Export CSV in the Data Summary table
The export includes raw numbers for Excel compatibility, with dates as columns in pivot format.

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Integration

Last modified on April 24, 2026