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USE CASE: E-COMMERCE & RETAIL

Secure AI for retail & commerce

Automate customer support and product recommendations while protecting customer data, preventing refund fraud, and blocking competitor price scraping.

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ABUSE, COUNTED PER CLIENTschematic
requests, per client fingerprintfp 7a3cfp 1e90fp b204fp 55daper-key ceilingthrottledand independently, of every single requestwire transfer · gift-card codes · credential harvestingblocked on one message
Retail abuse is a rate-and-identity problem before it is a content problem. Requests are counted per fingerprint against your key's ceiling, and the fraud patterns are checked independently, because one well-worded refund scam does not arrive in a burst.

Where a retail assistant is exposed

  1. 01

    Customer Data Protection

    Redact card numbers, emails, phone numbers and other customer identifiers with a fixed shape before AI processing.

  2. 02

    Refund Fraud Prevention

    Detect social engineering and manipulation aimed at your return and refund policies.

  3. 03

    Per-Customer Blocking

    Block a customer or IP that abuses your assistant with one access-list rule, without redeploying your app.

  4. 04

    Per-Customer Risk

    See which customers keep getting flagged, with a risk band for each, so you find abuse before it scales.

  5. 05

    Prompt Injection Defense

    Stop customers from talking your assistant out of its instructions, into revealing its system prompt, or into promises it should not make.

  6. 06

    Agent Tool-Call Checks

    Validate an AI agent's tool calls, such as issuing a refund, before they run. Calls that need a person come back marked for human review.

Why PromptGuard for e-commerce?

  • Fraud and social-engineering detection
  • Customer data protection built-in
  • Per-customer access lists
  • Per-customer risk rollups
  • Scales with peak traffic

How it works for e-commerce

  1. 01

    Integrate

    Connect PromptGuard to your customer service AI, chatbots, and recommendation engines.

  2. 02

    Protect

    Turn on PII redaction and fraud detection, and add access-list rules for abusive customers.

  3. 03

    Scale

    Handle peak traffic securely. Automated protection that scales with your business.

Securing e-commerce AI

python
from promptguard import GuardClient

guard = GuardClient()  # reads PROMPTGUARD_API_KEY

# PII redaction and fraud detection are set on the project. Send the
# customer's id so abusive customers show up per end-user and can be
# blocked with one access-list rule.
messages = [{"role": "user", "content": customer_message}]
decision = guard.scan(messages, direction="input")

if decision.blocked:
    raise PermissionError(f"Blocked: {decision.threat_type}")

# A redacted request comes back with the values replaced
messages = decision.redacted_messages or messages

The controls this sector runs on

Secure your e-commerce AI

Deploy AI for customer support and recommendations with enterprise-grade protection.

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