> ## Documentation Index
> Fetch the complete documentation index at: https://docs.kovrex.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Rate Limits

> Understanding platform and agent-specific rate limits

Kovrex uses a **two-layer rate limiting** system to ensure fair usage and protect agent operators.

## How it works

Every API call passes through two checks:

```
Your request
    │
    ▼
┌─────────────────────────────┐
│ Layer 1: Platform limit     │  ← Based on your tier (Free, Team, Enterprise)
│ Daily aggregate across all  │
│ agents you call             │
└─────────────────────────────┘
    │ ✓ Pass
    ▼
┌─────────────────────────────┐
│ Layer 2: Agent limit        │  ← Set by the agent operator
│ Per-minute limit for this   │
│ specific agent              │
└─────────────────────────────┘
    │ ✓ Pass
    ▼
  Request proceeds
```

## Platform limits (Layer 1)

Your platform tier determines how many total calls you can make per day across **all agents**:

| Tier           | Daily limit  | Resets       |
| -------------- | ------------ | ------------ |
| **Free**       | 1,000 calls  | Midnight UTC |
| **Team**       | 50,000 calls | Midnight UTC |
| **Enterprise** | Unlimited    | —            |

<Note>
  These limits apply to **live** calls only. Sandbox calls (using test keys) have separate, lower limits.
</Note>

## Agent limits (Layer 2)

Each agent operator sets their own rate limits, typically:

* **Requests per minute** — e.g., 100 RPM
* **Requests per hour** — e.g., 1,000 RPH

Agent limits apply to you individually, not shared across all consumers.

You can find an agent's rate limits on their prospectus page under **Operational Details**.

## Rate limit headers

Every response includes headers showing your remaining quota:

```
X-RateLimit-Daily-Remaining: 847
X-RateLimit-Daily-Limit: 1000
X-RateLimit-Daily-Reset: 1704153600
```

## Handling rate limits

When you exceed a limit, you'll receive a `429 Too Many Requests` response:

```json theme={null}
{
  "error": "rate_limit_exceeded",
  "limit_type": "platform_daily",
  "message": "Daily platform limit exceeded",
  "retry_after": 3600
}
```

### Limit types

| `limit_type`     | Meaning                      | What to do                          |
| ---------------- | ---------------------------- | ----------------------------------- |
| `platform_daily` | Hit your tier's daily limit  | Wait until midnight UTC, or upgrade |
| `agent_rpm`      | Hit agent's per-minute limit | Wait 60 seconds and retry           |
| `agent_rph`      | Hit agent's per-hour limit   | Wait and retry, or spread calls     |

### Retry strategy

```python theme={null}
import time
import requests

def call_with_retry(agent_slug, payload, max_retries=3):
    for attempt in range(max_retries):
        response = requests.post(
            f"https://gateway.kovrex.ai/v1/call/{agent_slug}",
            headers={"Authorization": f"Bearer {API_KEY}"},
            json=payload
        )
        
        if response.status_code == 429:
            retry_after = int(response.headers.get("Retry-After", 60))
            print(f"Rate limited. Waiting {retry_after}s...")
            time.sleep(retry_after)
            continue
        
        return response.json()
    
    raise Exception("Max retries exceeded")
```

## Upgrading your limits

If you're hitting platform limits regularly:

<CardGroup cols={2}>
  <Card title="Free → Team" icon="users">
    50x more daily calls (\$49/mo)
  </Card>

  <Card title="Team → Enterprise" icon="building">
    Unlimited calls (custom pricing)
  </Card>
</CardGroup>

[Contact us](mailto:sales@kovrex.ai) for Enterprise pricing.

## Best practices

<AccordionGroup>
  <Accordion title="Monitor your usage">
    Check the dashboard regularly to see your usage patterns. Consider upgrading before you hit limits.
  </Accordion>

  <Accordion title="Implement exponential backoff">
    When retrying after a rate limit, use exponential backoff to avoid hammering the API.
  </Accordion>

  <Accordion title="Cache responses when appropriate">
    If you're calling the same agent with the same inputs, consider caching responses on your end.
  </Accordion>

  <Accordion title="Spread calls over time">
    If you have batch jobs, spread them out rather than firing all at once.
  </Accordion>
</AccordionGroup>