AI

curl -N -X POST https://playground.kaireonai.com/api/v1/ai/chat \
  -H "Content-Type: application/json" \
  -H "X-Tenant-Id: my-tenant" \
  -d '{
    "messages": [{ "role": "user", "content": "What are my top performing offers?" }],
    "route": "/dashboards"
  }'

[
  {
    "id": "conv_abc123",
    "title": "What are my top performing offers?",
    "userId": "user_001",
    "createdAt": "2026-03-18T10:30:00Z",
    "updatedAt": "2026-03-18T10:35:00Z",
    "user": { "name": "Admin User", "image": null }
  }
]

{
  "id": "conv_abc123",
  "title": "What are my top performing offers?",
  "tenantId": "my-tenant",
  "userId": "user_001",
  "createdAt": "2026-03-18T10:30:00Z",
  "updatedAt": "2026-03-18T10:35:00Z",
  "messages": [
    { "role": "user", "content": "What are my top performing offers?", "createdAt": "2026-03-18T10:30:00Z" },
    { "role": "assistant", "content": "Based on the data...", "toolInvocations": [...], "createdAt": "2026-03-18T10:30:05Z" }
  ]
}

{ "ok": true }

{
  "requiresConfirmation": true,
  "tier": "ml_worker",
  "warning": "Dataset has 50,000 rows. For datasets over 5,000 rows, enable the ML Worker for faster and cheaper analysis.",
  "confirmationMeta": {
    "rowCount": 50000,
    "accuracy": "ML Worker uses K-Means clustering, logistic regression, and TF-IDF -- more accurate than LLM pattern matching for large datasets.",
    "costEstimate": "Proceeding with LLM will use approximately 3,750,500 tokens (~$0.56).",
    "speedComparison": "ML Worker processes locally in seconds vs LLM round-trip latency."
  }
}

{
  "results": [
    { "name": "High-Value Loyalists", "description": "...", "size": 2340, "percentage": 18, "filterRules": [...], "characteristics": [...], "suggestedUse": "..." }
  ],
  "source": "llm",
  "analysisType": "segments",
  "recommendations": [
    { "id": "rec_...", "type": "segment", "title": "...", "status": "new", "source": "llm" }
  ],
  "recommendationsCreated": 3,
  "recommendationsSkipped": 1
}

{
  "jobId": "job_abc123",
  "source": "ml_worker",
  "analysisType": "segments"
}

{
  "segmentation": {
    "minClusters": 2,
    "maxClusters": 8,
    "algorithm": "kmeans",
    "includedFeatures": null
  },
  "policy": {
    "dailyCap": 3,
    "weeklyCap": 10,
    "monthlyCap": 30,
    "lookbackDays": 90,
    "minSampleSize": 100
  },
  "content": {
    "minImpressions": 100,
    "metricWeights": { "ctr": 0.33, "cvr": 0.34, "revenue": 0.33 },
    "confidenceLevel": 0.95
  },
  "ruleBuilder": {
    "maxConditions": 5,
    "allowedOperators": ["equals", "gt", "lt", "gte", "lte", "contains", "in"],
    "fieldTypeConstraints": null
  },
  "ranking": {
    "lagrangianEnabled": false,
    "crossOfferEnabled": false,
    "exp3IxEnabled": false,
    "budgetPacingEnabled": false,
    "goalSeekEnabled": false
  }
}

{
  "segmentation": { "maxClusters": 12 },
  "policy": { "lookbackDays": 180 },
  "ranking": { "lagrangianEnabled": true }
}

{
  "tenantId": "tenant_001",
  "analyzedAt": "2026-03-26T15:34:24.991Z",
  "insights": [
    {
      "id": "policy-blocks-offer_001",
      "type": "policy_blocks_top_offer",
      "severity": "warning",
      "title": "Category suppression may limit \"Win-Back Lapsed Policy\"",
      "description": "\"Win-Back Lapsed Policy\" has a 9.8% CVR (top performer) but category suppression may be blocking repeat impressions.",
      "impact": "Potential revenue loss: relaxing this policy for high-value customers could increase conversions by 10-20%.",
      "action": {
        "label": "Review Policy",
        "type": "navigate",
        "href": "/studio/contact-policies"
      },
      "entities": [
        { "type": "offer", "id": "offer_001", "name": "Win-Back Lapsed Policy" },
        { "type": "contactPolicy", "id": "cp_001", "name": "Category Suppression After Dismiss" }
      ]
    }
  ],
  "summary": { "total": 4, "critical": 0, "warning": 4 }
}

{
  "entities": [
    {
      "type": "qualification_rule",
      "name": "Age >= 25",
      "payload": {
        "conditions": [{ "field": "customer.age", "operator": "gte", "value": 25 }],
        "ruleType": "hard"
      }
    },
    {
      "type": "behavioral_metric",
      "name": "total_spend_90d",
      "payload": {
        "aggregation": "sum",
        "field": "revenue",
        "windowDays": 90,
        "description": "Sum of revenue from conversions over the last 90 days"
      }
    },
    {
      "type": "qualification_rule",
      "name": "Spend >= $500 (90d)",
      "payload": {
        "conditions": [{ "field": "total_spend_90d", "operator": "gte", "value": 500 }],
        "ruleType": "hard"
      }
    }
  ],
  "warnings": [
    "No 'age' field found in available schemas. The rule may not work until the field is added."
  ]
}

curl -X POST https://playground.kaireonai.com/api/v1/ai/parse-rule \
  -H "Content-Type: application/json" \
  -H "X-Tenant-Id: my-tenant" \
  -d '{ "text": "Only show to customers over 25 who spent more than $500 in the last 90 days and haven'\''t converted on credit card offers" }'

{
  "recommendations": [
    {
      "id": "rec_001",
      "tenantId": "my-tenant",
      "type": "policy",
      "title": "Set frequency cap to 3/week",
      "description": "Analysis of 12,500 interactions shows conversion rate peaks at 3 contacts/week (8.2%). Rate drops 65% at 7 contacts/week.",
      "payload": {
        "ruleType": "frequency_cap",
        "scope": "global",
        "maxContactsPerWeek": 3
      },
      "confidence": "high",
      "source": "llm",
      "status": "new",
      "metadata": {
        "frequencyBands": [
          { "contactsPerWeek": 1, "conversionRate": 0.05 },
          { "contactsPerWeek": 3, "conversionRate": 0.082 }
        ],
        "estimatedImpact": "Applying this cap would optimize contact frequency for better conversion."
      },
      "createdAt": "2026-03-18T10:00:00Z"
    }
  ]
}

{
  "recommendation": { "id": "rec_001", "type": "policy", "title": "...", "status": "new", ... }
}

{
  "recommendation": { "id": "rec_001", "status": "reviewed", ... }
}

{
  "entityId": "cp_001",
  "entityType": "policy"
}

{ "ok": true, "result": { "...": "the executed mutation's result" } }

{
  "connected": true,
  "url": "https://ml-worker.internal:8080"
}

{
  "connected": false
}

{
  "configured": true,
  "provider": "openai"
}

curl https://playground.kaireonai.com/api/v1/ai/config-status \
  -H "X-API-Key: krn_your_api_key" \
  -H "X-Tenant-Id: 5a9904b9-..."

{
  "ok": true,
  "applyId": "apl_abc123",
  "createdEntityIds": [
    { "entityType": "offer", "entityId": "off_xyz" }
  ],
  "mergedEntityIds": [
    { "entityType": "creative", "entityId": "crv_def" }
  ],
  "skippedProposalIds": ["prop_111", "prop_222"]
}

{
  "ok": false,
  "status": "rolled_back",
  "failedProposalId": "prop_888",
  "errorMessage": "creative.templateType is required",
  "errorField": "templateType"
}

{
  "ok": true,
  "applyId": "apl_abc123",
  "deletedEntityIds": [
    { "entityType": "offer", "entityId": "off_xyz" }
  ],
  "skippedMerges": [
    { "entityType": "creative", "entityId": "crv_def" }
  ],
  "orphanedRefusals": [
    {
      "entityType": "offer",
      "entityId": "off_old",
      "reason": "Foreign key constraint: 14 child interactionHistory rows reference this offer"
    }
  ]
}