How to redact sensitive API data before it reaches an AI agent

Loggie can replace selected fields in an API's JSON response before returning it to an AI agent. An administrator configures response-redaction rules in the access policy, using field names, JSON paths, or regular expressions that match field names and paths.

A support analysis might need ticket IDs and categories without customer email addresses. Redaction lets you preserve the fields the task needs while replacing specified values with a marker such as [REDACTED].

These rules do not automatically detect personal information. You choose the fields, test the result, and decide whether the remaining response is appropriate for the employee and AI tool receiving it.

Start with the data the task needs

For a report on recurring support questions, write down which fields are necessary. A ticket ID lets someone open the source record. Its status and category may support grouping. A customer's email address usually adds nothing to the report.

Asking an agent to omit email addresses from its final answer still lets those addresses reach the harness first. Redacting the selected field before returning the response prevents that exposure through this request path.

Prefer provider-side field selection when the API supports it, and grant only the operations the task requires. Redaction complements access permissions; it does not make an otherwise inappropriate endpoint safe by default.

A concrete before-and-after example

The following is synthetic JSON, not a response from a customer account:

{
  "id": "ticket_demo_42",
  "status": "open",
  "category": "delivery",
  "customer": {
    "id": "customer_demo_7",
    "name": "Example Customer",
    "email": "customer@example.test"
  },
  "notes": "Please call 202-555-0142 about the delivery."
}

Suppose the report needs the ticket fields and a stable customer reference, but no name, email, or notes. In Loggie's policy editor, open Response redaction and add these rules:

Rule type	Match	Replacement
JSON path	customer.name	[REDACTED]
JSON path	customer.email	[REDACTED]
Field name	notes	[REDACTED]

With those rules, the expected response is:

{
  "id": "ticket_demo_42",
  "status": "open",
  "category": "delivery",
  "customer": {
    "id": "customer_demo_7",
    "name": "[REDACTED]",
    "email": "[REDACTED]"
  },
  "notes": "[REDACTED]"
}

The object structure remains, and selected values become the replacement string. A matched object can also be replaced wholesale. If the report needs nothing inside customer, matching customer is simpler than maintaining a rule for each child.

Removing the notes field sacrifices its contents. That may be the right choice for a category-count report and the wrong choice for an analysis of what customers wrote. Resolve that tradeoff before giving the agent access to the response.

Choose the right match type

A Field name rule for email matches fields with that name wherever they occur, without regard to case. This is convenient when multiple objects contain the same field. It can also remove more than you intended, so test nested responses.

A JSON path rule selects a location. customer.email targets that nested field. For a response containing an items array, items[*].customer.email targets customer email fields within its entries. These paths omit the $ prefix used by some JSONPath libraries. Do not assume arbitrary JSONPath filters are supported.

Regex rules match field names or paths. They do not scan every string value for email addresses, credit-card numbers, or phone numbers. An email-pattern regex will not scrub an address embedded in a message string merely because the string looks like an email address.

Use the simplest matcher that expresses the policy. An exact path is easier to review than a broad regex. Rules use the first match, so review their order when you configure overlapping patterns with different replacement values.

Free text needs a separate decision

In the synthetic input above, removing customer.email leaves the phone number in notes untouched. Real ticket messages can repeat names and contact details that also appear in structured fields.

If the task does not need a text field, redact the entire field. If it does, decide whether that content is permitted in the chosen AI environment. You may need a separate, validated content-sanitization process before allowing it through. Do not describe field matching as automatic anonymization.

Even a response without direct contact details may remain identifiable. A stable customer ID can connect records, and a distinctive combination of transaction details can identify someone. Keep those fields only when the workflow needs them and your data policy permits them.

The Klaviyo and Gorgias reporting walkthrough shows why this matters: a report can use ticket references and paraphrased themes, while the source conversations still deserve careful access control.

Test from the agent's side

Use a synthetic fixture or a safe test account before trying a new rule against sensitive production responses.

1. Save the rules on the policy assigned to the intended profile and connection.
2. Make a permitted read through that profile using the Loggie CLI.
3. Inspect the returned JSON. Check the exact fields and nested arrays you meant to redact.
4. Confirm that fields needed for the task remain useful. Replacing a number or object with a string can affect downstream parsing.
5. Try missing fields, mixed-case field names, and more than one array item. Check overlapping rules.
6. Test other response shapes the endpoint can return, including errors and alternate formats.

A REST endpoint returning CSV, HTML, a PDF, or another non-JSON format is outside this JSON-redaction mechanism. Loggie's REST redaction path passes non-JSON responses through unchanged. If those responses would expose prohibited data, restrict that operation or handle the format through another reviewed process.

Recheck the rules when a provider changes its response structure. A new field called contact_email will not necessarily match a rule for email.

What redaction does not cover

These rules apply to responses traveling through the configured Loggie access path. They do not alter the provider's stored records, erase existing downloads, or constrain a separate connector using its own credentials.

Logging deserves its own review. Do not infer that agent-facing redaction automatically applies to every stored request body, response body, or diagnostic record. Check your audit-log configuration, especially before enabling body logging.

For the support example, check that the agent can count delivery tickets and cite their IDs while the selected name, email, and notes fields arrive as [REDACTED]. Save that fixture with your policy review so a future change can be checked against the same expected output.