Integration guide

This guide explains how to integrate external systems with Tracer, including the payload requirements, integration flow, and best practices for achieving optimal performance.

Integration overview

Tracer is designed to be called by authorization systems (payment gateways, workflow orchestrators, or transaction processors) that need real-time validation decisions. The integration follows a simple request-response pattern:

Key principle: Tracer does not fetch external data during validation. Your system is responsible for providing all context needed for rule evaluation.

Payload-Complete Pattern

Tracer uses the Payload-Complete Pattern, which means all context required for validation must be included in the request. This design ensures:

Benefit	Description
Predictable latency	No external calls during validation; response time stays under 80ms
Simplicity	Single request contains everything needed for decision
Reliability	No dependency on external services during validation
Flexibility	Your system controls data freshness and enrichment logic

Your responsibilities

As the integrating system, you are responsible for:

Enriching the payload with account, segment, portfolio, and merchant data before calling Tracer
Providing accurate context for rule and limit evaluation—Tracer cannot fetch missing data
Handling the decision (ALLOW, DENY, or REVIEW) appropriately in your workflow
Implementing retry logic if Tracer is temporarily unavailable
Managing review workflows when Tracer returns REVIEW—Tracer does not include case management

Tracer validates what you send. If your payload is missing context (e.g., account status, segment membership), rules that depend on that data cannot evaluate correctly. Always ensure payloads are complete before submission.

Tracer’s responsibilities

Tracer is responsible for:

Evaluating rules against the provided context
Checking limits against current usage
Recording audit trail for compliance
Returning decision with detailed information

Integration flow

Follow these steps to integrate your system with Tracer.

Step 1: Prepare the transaction context

Before calling Tracer, gather all relevant data from your systems:

Step 2: Call Tracer API

Send a POST request to /v1/validations with the complete transaction context including:

Transaction details (type, subType, amount, currency, timestamp)
Account information (required)
Optional: segment, portfolio, merchant, and custom metadata

For complete payload structure and field details, see the API reference.

Step 3: Handle the response

Process the decision returned by Tracer:

Decision	Action
`ALLOW`	Proceed with the transaction
`DENY`	Reject the transaction; show reason to user if appropriate
`REVIEW`	Queue for manual review in your review system

The response includes the validationId for audit trail correlation, details about which rules matched, and current limit usage information.

Using metadata

Metadata allows you to pass custom fields that your rules can evaluate. Use this for context like channel, device information, customer tier, or any business-specific attributes.

Metadata keys must be alphanumeric with underscores only, maximum 64 characters. Maximum 50 entries per request.

Performance considerations

Optimize your integration for low latency and high reliability.

Timeout budget

Tracer is designed to respond in under 80ms (p99). Configure your client timeout accordingly:

Configuration	Recommended value
Client timeout	100ms
Connection timeout	50ms
Read timeout	100ms

Retry strategy

Implement retry logic for transient failures:

On 5xx error or timeout:
  - Wait 10ms
  - Retry once
  - If still failing, apply fallback policy

Do not retry on 4xx errors—these indicate invalid requests that will fail again.

Fallback behavior

Decide what happens when Tracer is unavailable:

Strategy	When to use
Fail-open	Allow transaction if Tracer is down (prioritize availability)
Fail-closed	Deny transaction if Tracer is down (prioritize security)
Queue for review	Queue transaction for manual review

Your choice depends on your risk tolerance and business requirements.

Data freshness

Since you control the payload enrichment, data freshness is your responsibility. Tracer trusts the data you provide and cannot detect stale information.

Data type	Freshness recommendation	Risk if stale
Account status	Real-time or near real-time	Transactions on suspended accounts may be allowed
Segment membership	Can be cached (changes infrequently)	Wrong limits or rules may apply
Portfolio assignment	Can be cached (changes infrequently)	Incorrect scope matching
Merchant data	Can be cached with periodic refresh	Risk rules may not trigger correctly

Stale data leads to incorrect decisions. If an account was suspended but your cache shows it as active, Tracer will allow transactions that should be denied. Your enrichment layer is the source of truth for Tracer.

Date and time format

All datetime fields must use RFC3339 format with mandatory timezone: Valid formats:

2026-01-30T10:30:00Z           (UTC)
2026-01-30T10:30:00-03:00      (São Paulo timezone)
2026-01-30T00:00:00+00:00      (UTC explicit)

Invalid formats:

2026-01-30                     (date only - rejected)
2026-01-30T10:30:00            (missing timezone - rejected)

Integration checklist

Before going to production, verify:

API Key is configured and secured
Client timeout is set to 100ms
Retry logic is implemented for 5xx errors
Fallback behavior is defined
All required fields are populated
Timestamps use RFC3339 format with timezone
Currency codes are uppercase ISO 4217
Decision handling is implemented (ALLOW/DENY/REVIEW)
Validation IDs are logged for audit trail correlation

Example integration (pseudocode)

def validate_transaction(transaction):
    # Step 1: Enrich payload
    payload = {
        "requestId": generate_uuid(),
        "transactionType": transaction.type,
        "amount": transaction.amount,
        "currency": transaction.currency.upper(),
        "timestamp": now_rfc3339(),
        "account": get_account_context(transaction.account_id),
        "segment": get_segment_context(transaction.segment_id),
        "merchant": get_merchant_context(transaction.merchant_id),
        "metadata": transaction.custom_fields
    }

    # Step 2: Call Tracer
    try:
        response = http_post(
            url="https://tracer.example.com/v1/validations",
            headers={"X-API-Key": API_KEY},
            json=payload,
            timeout_ms=100
        )
    except Timeout:
        return apply_fallback_policy()
    except ServerError:
        return retry_once_or_fallback()

    # Step 3: Handle decision
    if response.decision == "ALLOW":
        return proceed_with_transaction()
    elif response.decision == "DENY":
        return reject_transaction(response.reason)
    elif response.decision == "REVIEW":
        return queue_for_manual_review(response.validationId)

Next steps

Rules engine - Create rules that evaluate against the context you provide
Spending limits - Configure limits that apply to your transaction scopes
Audit and compliance - Query validation history and audit trail

​Integration overview

​Payload-Complete Pattern

​Your responsibilities

​Tracer’s responsibilities

​Integration flow

​Step 1: Prepare the transaction context

​Step 2: Call Tracer API

​Step 3: Handle the response

​Using metadata

​Performance considerations

​Timeout budget

​Retry strategy

​Fallback behavior

​Data freshness

​Date and time format

​Integration checklist

​Example integration (pseudocode)

​Next steps

Integration overview

Payload-Complete Pattern

Your responsibilities

Tracer’s responsibilities

Integration flow

Step 1: Prepare the transaction context

Step 2: Call Tracer API

Step 3: Handle the response

Using metadata

Performance considerations

Timeout budget

Retry strategy

Fallback behavior

Data freshness

Date and time format

Integration checklist

Example integration (pseudocode)

Next steps