How does LLM budget enforcement work in Cognocient?

LLM budget enforcement means stopping AI spend before it happens, not flagging it after. Cognocient checks every API call against your configured budgets before the call reaches the provider. Set a budget in the dashboard and choose your enforcement mode: Block (hard stop), Degrade (auto-switch to cheaper model), or Alert (allow through, flag it).

What are the three budget enforcement modes?

How do I create a budget in Cognocient?

Go to Dashboard → Budgets → New Budget and fill in:

• Name — descriptive label, e.g. chatbot feature, Engineering department, Org total
• Scope — Global (all traffic), Feature (by X-Cost-Feature), Department (by X-Cost-Department), User (by X-Cost-User), Environment (by X-Cost-Environment), or Key (one proxy key, Growth+)
• Monthly limit — the spending cap in USD
• Enforcement mode — Alert, Block, or Degrade
• Alert thresholds — default 50%, 80%, 100% — each one alerts once per month by email (every plan) and Slack (Base+); see Alerts

Alert mode

All API calls pass through normally. Cognocient sends an alert when each configured threshold is crossed: by email to the account owner by default, and to Slack if connected.

What the alert says (email subject "Cognocient: 🟡 Budget Alert — 80%"):

🟡 Budget Alert — 80%
Budget: Ticket resolver
Applies to: feature: ticket-resolver
Spent this month: $402.10 of $500.00
[View in Cognocient →]

Block mode

When the budget is exhausted, Cognocient returns HTTP 429 immediately. The AI provider never sees the request — overspend is structurally impossible.

{
  "error": {
    "message": "Budget exceeded for feature 'chatbot'. Monthly limit: $500.00",
    "type": "budget_exceeded",
    "feature": "chatbot",
    "current_spend": 502.14,
    "limit": 500.00,
    "reset_at": "2026-07-01T00:00:00Z"
  }
}

Handle it gracefully in your application:

Degrade mode (recommended for production)

When the budget threshold is reached, Cognocient transparently rewrites requests to a cheaper model. Your application keeps working — cost drops immediately.

The response includes headers so you can optionally surface a UI indicator:

x-cog-degraded: true
x-cog-original-model: gpt-4o
x-cog-degraded-model: gpt-4o-mini

Budget scopes

Stack budgets. A feature budget of $800/mo and a department budget of $2,000/mo coexist — both are checked, the most restrictive wins. See Hierarchical Budgets for how to set up nested limits.

Per-run limits for agents

For agentic workloads, add a per-run limit so a single runaway agent execution can't consume your entire monthly budget.

Configure in Budgets → New Budget → Per-run limit. When a run exceeds its limit, only that run is blocked — other concurrent runs continue normally.

Pass X-Cost-Run-ID on all agent calls (see Track Cost Per Agent Run).

Check remaining budget before your next agent step

For long-running agents, query remaining budget before each step to exit gracefully instead of being hard-stopped mid-execution:

import httpx
 
async def check_budget(feature: str, run_id: str) -> bool:
    status = (await httpx.AsyncClient().get(
        "https://api.cognocient.com/api/budgets/status",
        headers={"Authorization": f"Bearer {COGNOCIENT_KEY}"},
        params={"feature": feature, "run_id": run_id},
    )).json()
 
    if not status["can_proceed"]:
        return False
    # Stop if any budget is below $0.05 remaining
    return all(b["remaining_usd"] > 0.05 for b in status.get("budgets", []))
 
# In your agent loop:
for step in planned_steps:
    if not await check_budget("research-agent", run_id):
        return {"status": "budget_limit_reached", "completed": completed}
    result = await execute_step(step)

Frequently asked questions