Spending Policies for Autonomous AI Agents: Control Without Micromanagement

Giving an AI agent the ability to spend money is easy. Controlling how much, where, and when — that's the real problem.

Traditional expense management tools were built for human employees. You set a monthly limit, maybe restrict some merchant categories, and review receipts at the end of the month. That works when your team is five people with corporate cards.

It doesn't work when your team includes AI agents that can make hundreds of transactions per day.

Why AI agents need different controls

Human spending follows predictable patterns. People buy lunch, book flights, subscribe to software. The amounts are normal. The frequency is low. When something looks off, a human reviewer catches it.

AI agents break every one of these assumptions:

• Volume — an agent can make 50 purchases in a minute
• Unpredictability — agents may interpret instructions creatively, buying things outside their intended scope
• No self-regulation — an agent doesn't pause and think "this seems expensive"
• Prompt vulnerability — a compromised prompt can redirect spending to unintended merchants

Without infrastructure-level controls, the gap between "the agent can buy" and "the agent is buying everything" is one bad prompt away.

Ovra's policy engine

Ovra enforces spending policies at the infrastructure layer — before any card is issued, before any money moves. The agent cannot bypass these controls regardless of what instructions it receives.

Per-transaction limits

Set maximum amounts per individual transaction. An agent trying to charge more than the limit is simply denied.

Max per transaction: €500
Agent requests: €750
Result: Denied

Daily and monthly aggregate limits

Cap total spending across all transactions within a time window.

Daily limit: €2,000
Spent today: €1,800
Agent requests: €400
Result: Denied (would exceed daily limit)

Per-agent budgets

Each AI agent gets its own independent budget. Your travel agent has different limits than your procurement agent.

agent_travel: €5,000/month
agent_procurement: €20,000/month
agent_subscriptions: €1,000/month

Merchant category codes (MCC)

Restrict which types of merchants an agent can pay. A subscription manager should only pay software companies, not restaurants.

Allowed MCCs: [5734, 5817, 7372]  // Software, SaaS, Computer services
Blocked MCCs: [5812, 5813]         // Restaurants, Bars

Time-window restrictions

Limit when agents can transact. No purchases outside business hours, no weekend spending, no transactions during maintenance windows.

Approval workflows

For high-value transactions, require human confirmation before the card is issued. The agent submits the request, the human approves or denies it, and only then does the transaction proceed.

Policy enforcement architecture

Traditional expense tools apply policies after the fact — flagging unusual transactions for review. By the time you see the flag, the money is already gone.

Ovra's architecture is different:

1. Agent requests a transaction
2. Policy engine evaluates all active rules
3. If any rule fails → transaction denied, no card issued
4. If all rules pass → single-use card created with exact amount
5. Card is used and immediately destroyed
6. Full audit log captured

The key difference: policies are enforced before the money moves, not after.

API-driven policy management

Policies are managed through Ovra's API, so they can be updated programmatically:

await ovra.policies.update("agent_travel", {
  maxPerTransaction: 50000,
  dailyLimit: 200000,
  allowedMCCs: [3000, 3001, 3002, 4511, 7011],
  requireApprovalAbove: 100000,
  activeHours: { start: "06:00", end: "22:00", timezone: "Europe/Berlin" }
});

This means your own systems can dynamically adjust agent budgets based on business rules, seasonal patterns, or real-time risk signals.

Automated expense reporting

Every transaction through Ovra includes full context:

• Which agent made the request
• What spending policy was applied
• Whether approval was required (and who approved)
• The purpose/reason for the purchase
• Merchant details and category
• Timestamp and amount

This creates an automatic expense report — no manual receipt collection, no missing context, no "I don't remember why I bought this."

Tools for automated expense control in Germany

For German companies specifically, Ovra provides:

• GDPR-compliant data handling — all transaction data processed in the EU
• German language dashboard — full visibility in your preferred language
• Euro-native — no currency conversion fees for EUR transactions
• BaFin-aligned compliance — meeting German regulatory requirements

Getting started

Define your spending policies before your agents start transacting. Ovra's policy engine is configured through the API or dashboard, and applies immediately to all new transactions.

Currently in private beta. Join the waitlist.