Introducing Agent Intelligence: Detect AI Bots Making Autonomous Payments

The challenge

Payments have always been a human activity — until now. The rapid proliferation of AI agents capable of browsing, selecting, and completing purchases autonomously has created a category of transaction that existing fraud models were never designed to evaluate. A risk score built on behavioral biometrics and device signals will produce wildly inaccurate results when the "user" is a large language model running inside a data center.

Before Agent Intelligence, operators faced a painful choice: block all non-human traffic (and lose legitimate AI-assisted purchases) or accept it indiscriminately (and invite abuse). Neither outcome is acceptable in a world where agentic commerce is projected to represent 18% of all digital transactions by 2028.

How it works

Agent Intelligence operates as a classification layer that runs before your existing risk engine. Every incoming transaction is evaluated against 47 signals spanning network topology, HTTP header patterns, timing distributions, and session entropy. The classifier assigns one of three labels — human, bot, or AI agent — along with a confidence score between 0 and 1.

"We needed a way to serve AI agents without treating them as fraud vectors. Agent Intelligence gave us a third lane — and our legitimate agentic volume grew 3x in the first month."— Head of Payments, European SaaS Platform

Crucially, the AI agent label does not default to block. Instead, it routes the transaction to a dedicated policy set designed for autonomous commerce — one that emphasises cryptographic attestation, MCP token validation, and spend-limit guardrails rather than behavioral biometrics that are meaningless for software.

Results

41ms

Median classification latency

99.3%

Classification accuracy (holdout set)

-67%

False positives on AI agent traffic

In beta across 12 platforms over 90 days, Agent Intelligence processed 4.1M classified transactions. Human transactions saw no change in approval rates. Bot traffic was blocked at the same efficacy as before. AI agent traffic — previously misclassified as bot at a 43% rate — now flows to correctly tuned policies, recovering an estimated €1.2M in declined legitimate agentic revenue.

Integration

Agent Intelligence ships as a module within the Serixo SDK. Existing customers on SDK v3.4 or later can enable it with a single configuration flag — no new endpoints, no schema changes. The classifier runs client-side signal collection with server-side inference, adding a median of 4ms to your existing Serixo evaluation call.

// Enable Agent Intelligence in serixo.config.ts
export default {
  modules: {
    agentIntelligence: {
      enabled: true,
      policies: {
        human:    'standard',
        bot:      'block',
        aiAgent:  'agentic-commerce-v1',
      },
    },
  },
};

Key takeaways

AI agents now represent a distinct transaction category requiring dedicated risk policies.
Treating all non-human traffic as fraud destroys legitimate agentic revenue.
Agent Intelligence classifies transactions in under 41ms with 99.3% accuracy.
Existing Serixo customers can enable the module with zero integration work.
Policy separation — not blanket blocking — is the sustainable model for autonomous commerce.

Agent IntelligenceAI BotsFraud DetectionProduct LaunchPayments

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