Submit a standardized inbound notification

curl --request POST \
  --url https://sandbox.theary.ai/background-check/v1/inbound/notifications \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "messageData": {
    "from": "hr@techcorp.com",
    "to": "verify@theary.ai",
    "subject": "Re: Employment Verification Request for John Smith",
    "body": {
      "text": "John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.",
      "html": "<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>"
    },
    "timestamp": "2026-01-10T10:30:00Z"
  },
  "metadata": {
    "searchId": "search_abc123",
    "applicantName": "John Smith"
  }
}
'

import requests

url = "https://sandbox.theary.ai/background-check/v1/inbound/notifications"

payload = {
    "messageData": {
        "from": "hr@techcorp.com",
        "to": "verify@theary.ai",
        "subject": "Re: Employment Verification Request for John Smith",
        "body": {
            "text": "John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.",
            "html": "<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>"
        },
        "timestamp": "2026-01-10T10:30:00Z"
    },
    "metadata": {
        "searchId": "search_abc123",
        "applicantName": "John Smith"
    }
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    messageData: {
      from: 'hr@techcorp.com',
      to: 'verify@theary.ai',
      subject: 'Re: Employment Verification Request for John Smith',
      body: JSON.stringify({
        text: 'John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.',
        html: '<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>'
      }),
      timestamp: '2026-01-10T10:30:00Z'
    },
    metadata: {searchId: 'search_abc123', applicantName: 'John Smith'}
  })
};

fetch('https://sandbox.theary.ai/background-check/v1/inbound/notifications', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://sandbox.theary.ai/background-check/v1/inbound/notifications",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'messageData' => [
        'from' => 'hr@techcorp.com',
        'to' => 'verify@theary.ai',
        'subject' => 'Re: Employment Verification Request for John Smith',
        'body' => [
                'text' => 'John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.',
                'html' => '<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>'
        ],
        'timestamp' => '2026-01-10T10:30:00Z'
    ],
    'metadata' => [
        'searchId' => 'search_abc123',
        'applicantName' => 'John Smith'
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://sandbox.theary.ai/background-check/v1/inbound/notifications"

	payload := strings.NewReader("{\n  \"messageData\": {\n    \"from\": \"hr@techcorp.com\",\n    \"to\": \"verify@theary.ai\",\n    \"subject\": \"Re: Employment Verification Request for John Smith\",\n    \"body\": {\n      \"text\": \"John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.\",\n      \"html\": \"<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>\"\n    },\n    \"timestamp\": \"2026-01-10T10:30:00Z\"\n  },\n  \"metadata\": {\n    \"searchId\": \"search_abc123\",\n    \"applicantName\": \"John Smith\"\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://sandbox.theary.ai/background-check/v1/inbound/notifications")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"messageData\": {\n    \"from\": \"hr@techcorp.com\",\n    \"to\": \"verify@theary.ai\",\n    \"subject\": \"Re: Employment Verification Request for John Smith\",\n    \"body\": {\n      \"text\": \"John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.\",\n      \"html\": \"<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>\"\n    },\n    \"timestamp\": \"2026-01-10T10:30:00Z\"\n  },\n  \"metadata\": {\n    \"searchId\": \"search_abc123\",\n    \"applicantName\": \"John Smith\"\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://sandbox.theary.ai/background-check/v1/inbound/notifications")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"messageData\": {\n    \"from\": \"hr@techcorp.com\",\n    \"to\": \"verify@theary.ai\",\n    \"subject\": \"Re: Employment Verification Request for John Smith\",\n    \"body\": {\n      \"text\": \"John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.\",\n      \"html\": \"<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>\"\n    },\n    \"timestamp\": \"2026-01-10T10:30:00Z\"\n  },\n  \"metadata\": {\n    \"searchId\": \"search_abc123\",\n    \"applicantName\": \"John Smith\"\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "messageId": "msg_001",
  "success": false,
  "failureReasons": ["metadata.searchRefId is required for JSON channel requests"],
  "processedAt": "2024-01-15T10:30:00.000Z"
}

POST

background-check

inbound

notifications

Submit a standardized inbound notification

curl --request POST \
  --url https://sandbox.theary.ai/background-check/v1/inbound/notifications \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "messageData": {
    "from": "hr@techcorp.com",
    "to": "verify@theary.ai",
    "subject": "Re: Employment Verification Request for John Smith",
    "body": {
      "text": "John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.",
      "html": "<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>"
    },
    "timestamp": "2026-01-10T10:30:00Z"
  },
  "metadata": {
    "searchId": "search_abc123",
    "applicantName": "John Smith"
  }
}
'

import requests

url = "https://sandbox.theary.ai/background-check/v1/inbound/notifications"

payload = {
    "messageData": {
        "from": "hr@techcorp.com",
        "to": "verify@theary.ai",
        "subject": "Re: Employment Verification Request for John Smith",
        "body": {
            "text": "John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.",
            "html": "<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>"
        },
        "timestamp": "2026-01-10T10:30:00Z"
    },
    "metadata": {
        "searchId": "search_abc123",
        "applicantName": "John Smith"
    }
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    messageData: {
      from: 'hr@techcorp.com',
      to: 'verify@theary.ai',
      subject: 'Re: Employment Verification Request for John Smith',
      body: JSON.stringify({
        text: 'John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.',
        html: '<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>'
      }),
      timestamp: '2026-01-10T10:30:00Z'
    },
    metadata: {searchId: 'search_abc123', applicantName: 'John Smith'}
  })
};

fetch('https://sandbox.theary.ai/background-check/v1/inbound/notifications', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://sandbox.theary.ai/background-check/v1/inbound/notifications",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'messageData' => [
        'from' => 'hr@techcorp.com',
        'to' => 'verify@theary.ai',
        'subject' => 'Re: Employment Verification Request for John Smith',
        'body' => [
                'text' => 'John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.',
                'html' => '<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>'
        ],
        'timestamp' => '2026-01-10T10:30:00Z'
    ],
    'metadata' => [
        'searchId' => 'search_abc123',
        'applicantName' => 'John Smith'
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://sandbox.theary.ai/background-check/v1/inbound/notifications"

	payload := strings.NewReader("{\n  \"messageData\": {\n    \"from\": \"hr@techcorp.com\",\n    \"to\": \"verify@theary.ai\",\n    \"subject\": \"Re: Employment Verification Request for John Smith\",\n    \"body\": {\n      \"text\": \"John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.\",\n      \"html\": \"<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>\"\n    },\n    \"timestamp\": \"2026-01-10T10:30:00Z\"\n  },\n  \"metadata\": {\n    \"searchId\": \"search_abc123\",\n    \"applicantName\": \"John Smith\"\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://sandbox.theary.ai/background-check/v1/inbound/notifications")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"messageData\": {\n    \"from\": \"hr@techcorp.com\",\n    \"to\": \"verify@theary.ai\",\n    \"subject\": \"Re: Employment Verification Request for John Smith\",\n    \"body\": {\n      \"text\": \"John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.\",\n      \"html\": \"<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>\"\n    },\n    \"timestamp\": \"2026-01-10T10:30:00Z\"\n  },\n  \"metadata\": {\n    \"searchId\": \"search_abc123\",\n    \"applicantName\": \"John Smith\"\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://sandbox.theary.ai/background-check/v1/inbound/notifications")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"messageData\": {\n    \"from\": \"hr@techcorp.com\",\n    \"to\": \"verify@theary.ai\",\n    \"subject\": \"Re: Employment Verification Request for John Smith\",\n    \"body\": {\n      \"text\": \"John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.\",\n      \"html\": \"<p>John Smith was employed at Tech Corp from January 2020 to June 2023 as a Software Engineer.</p>\"\n    },\n    \"timestamp\": \"2026-01-10T10:30:00Z\"\n  },\n  \"metadata\": {\n    \"searchId\": \"search_abc123\",\n    \"applicantName\": \"John Smith\"\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "messageId": "msg_001",
  "success": false,
  "failureReasons": ["metadata.searchRefId is required for JSON channel requests"],
  "processedAt": "2024-01-15T10:30:00.000Z"
}

Submit Inbound Notification

Use this endpoint to submit verification responses from external parties. The system processes responses through various channels (email, forms, fax, and generic JSON) and automatically extracts verification details using AI.

Authentication

Bearer Token Required - Include your JWT token in the Authorization header.

Quick Examples

# For employment verification
curl -sS -X POST "https://sandbox.theary.ai/background-check/v1/inbound/notifications" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -d '{
    "messageId": "msg_001",
    "threadId": "thread_001",
    "channel": "EMAIL",
    "messageData": {
      "id": "msg_001",
      "threadId": "thread_001",
      "from": "hr@company.com",
      "to": "verifications@theary.ai",
      "subject": "Employment Verification - John Doe",
      "body": {
        "text": "John Doe worked here from 2020-01-15 to 2023-12-31 as Software Engineer."
      },
      "timestamp": "2026-01-15T10:30:00.000Z"
    }
  }'

# For education verification
curl -sS -X POST "https://sandbox.theary.ai/background-check/v1/inbound/notifications" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "messageId": "msg_001",
    "threadId": "thread_001",
    "channel": "EMAIL",
    "messageData": {
      "id": "msg_001",
      "threadId": "thread_001",
      "from": "capelookouthighschool@edu.com",
      "to": "verifications@theary.ai",
      "subject": "Education Verification - John Doe",
      "body": {
        "text": "John Doe completed with a Highschool Diploma at Cape Lookout High School in Moorehead City NC with graduation date as 2023-05-15"
      },
      "timestamp": "2024-01-15T10:30:00.000Z"
    }
  }'

Request Parameters

Optional Fields

string

Unique identifier for this message. If not provided, the system will auto-generate one using the format msg_<timestamp>_<random>. You can also provide it in messageData.id - the system will use the top-level messageId if present, otherwise messageData.id, otherwise auto-generate.

string

Thread identifier to link related messages. If not provided, the system will use the messageId as the threadId. You can also provide it in messageData.threadId - the system will use the top-level threadId if present, otherwise messageData.threadId, otherwise use the messageId.

object

required

Message content and metadata

Show properties

string

Message ID (optional - will be auto-generated if not provided and matches top-level messageId)

string

Thread ID (optional - will be auto-generated if not provided and matches top-level threadId)

string

Sender email address. Required for non-JSON channels; optional for JSON channel requests.

string

Recipient email address (e.g., verifications@theary.ai). Required for non-JSON channels; optional for JSON channel requests.

string

required

ISO 8601 timestamp (e.g., 2026-01-15T10:30:00.000Z)

string

Email subject line

object

Message content with text and/or html fields. Used by email, fax, form, and ticketing channels. Not used for JSON channel extraction (use data instead).

object

Structured third-party provider payload for JSON channel requests. Required when channel is JSON. Pass the vendor response object as-is. The API enumerates employment or education history records from common vendor shapes (see Supported JSON payload shapes). An empty object fails with No JSON payload found.

array

File attachments (PDFs are supported and will be processed for text extraction). Each attachment should have: - id (string) - Unique attachment identifier - name (string) - Attachment filename - contentType (string) - MIME type (e.g., “application/pdf”) - size (number) - File size in bytes - content (string, optional) - Base64-encoded file content (required for PDF processing)

Optional Fields

string

Communication channel (defaults to STANDARD)
Available Values: STANDARD, EMAIL, EFORM, MICROSOFT_GRAPH, FAX_WEBHOOK, VOICE_TRANSCRIPT, TICKETING, JITBIT, JSON
Channel Types:

STANDARD - Default when channel is omitted
EMAIL - Email responses
EFORM - Electronic forms
MICROSOFT_GRAPH - Office 365
FAX_WEBHOOK - Fax responses
VOICE_TRANSCRIPT - Phone/voice transcription responses
TICKETING / JITBIT - Ticketing systems
JSON - Generic structured JSON payloads from upstream systems

object

Additional context data. Required fields depend on channel.

Show properties

string

Required for JSON channel. Identifies the verification search to update. Matched against the search’s externalSearchId or internal reference number. For JSON requests, the API uses this value exclusively and does not scan the payload for reference numbers in the message body.

string

Source system identifier (recommended for JSON channel traceability, e.g. equifax, thomas-and-company).

object

Pre-extracted verification data from upstream systems (non-JSON channels). When verifiedInfo is present, the API may skip re-extraction. See the OpenAPI schema for verificationResult values.

Attachments

Attachments are supported for PDF files. PDFs are automatically processed to extract text content, which is then used during message classification and verification data extraction. Supported Format:

PDF files (application/pdf) - Fully supported with text extraction
Other file types may be included but will not be processed

Attachment Processing:

PDFs are processed using document extraction tools
Extracted text is included in the message analysis
Processing errors are logged but do not block message processing

Response

string

Echo of the submitted message ID

boolean

Whether processing succeeded

object

AI-powered message classification
Fields:

type - Classification type (see Classification Types below)
confidence - Score from 0 to 1 indicating classification confidence
- reasoning - Explanation of the classification decision

object

Root-level highest-confidence normalized employment verification object, omitted from extractedData. This temporary backward-compatible shape applies to every channel. Each object includes backward-compatible flat provided* / verified* values (including applicant names and providedReasonLeft) and the canonical fields comparison map. See the EmploymentVerification object for field definitions.

object

Education counterpart to root-level employmentVerification, omitted from extractedData. This is the single highest-confidence provider education-history object for every channel. Each object includes backward-compatible flat provided* / verified* values and the canonical fields comparison map. See the EducationVerification object for field definitions.

employmentVerification and educationVerification temporarily return one object for backward compatibility. A future version will return sorted arrays after consumers migrate to the array contract.

object

Structured verification data extracted from the message. Present on successful processing for every channel, including JSON. Does not include duplicate employmentVerification / educationVerification objects when those are returned at the response root.

Show common fields

string

Normalized verification outcome (e.g. verified, no_record, third_party).

string

Extracted employer name (employment searches). Best-match scalar for JSON channel; same source as employmentVerification.

string

Extracted job title (employment searches).

string

Extracted employer location when present on the selected record.

string

Applicant name from the selected verification record.

object

Structured date mirror (startDate, endDate, etc.) for backward compatibility.

object

Structured content mirror (for example positionTitle) for backward compatibility.

object

Optional duplicate of scalar extraction fields for backward compatibility.

boolean

JSON channel. true when a critical mismatch is detected on the best-match history row under tenant comparison settings. Field-level comparison details are on root-level employmentVerification.fields / educationVerification.fields, not in extractedData.applicantMismatches and applicantDiscrepancies are not returned in webhook or inbound notification payloads (removed). Use fields.*.status, expected, extracted, and comparison on the verification object instead.

boolean

JSON channel. Present when a critical mismatch on the best-match record triggers manual review routing (applicantMismatch: true). May appear in both the synchronous response and downstream inbound-notification or action-required webhooks.

boolean

JSON channel. true when extractedData was produced from a structured third-party JSON payload rather than email/fax/voice extraction. Present in the synchronous response and downstream payloads.

array

Error messages if failed (empty array if successful)

object

Processing details including searchId, outcome, and channel

string

Processing completion timestamp (ISO 8601 format)

Classification Types

The classification type field is one of the INTENT enum values assigned by the inbound processing pipeline:

VERIFICATION - Verification confirmed with details
INFO_REQUEST - Employer/school needs more information, or a general information request
INFO_PROVIDED - Applicant provided information that may need follow-up
NEXT_CONTACT - Indicates a different contact at the entity should be reached next
WRONG_ENTITY - Message indicates the wrong organization/entity was contacted
RECORD_NOT_FOUND - No employment/education record found
AUTHORIZATION_FORM_REQUEST - Authorization form is needed before the entity will respond
NO_ACTION_REQUIRED - Message requires no further action
UNKNOWN - Could not determine intent
OTHER - Other classification that doesn’t fit the above

THIRD_PARTY is a deprecated legacy value — the classifier remaps it to WRONG_ENTITY internally, so it will never appear in a response’s classification.type.

Examples

Employment Verification

curl -sS -X POST "https://sandbox.theary.ai/background-check/v1/inbound/notifications" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -d '{
    "messageId": "emp_001",
    "threadId": "thread_abc",
    "channel": "EMAIL",
    "messageData": {
      "id": "emp_001",
      "threadId": "thread_abc",
      "from": "hr@techcorp.com",
      "to": "verifications@theary.ai",
      "subject": "Re: Employment Verification - John Doe",
      "body": {
        "text": "Reference: 11111111\n\nJohn Doe was employed as Software Engineer from 2020-01-15 to 2023-12-31. Employee ID: EMP001."
      },
      "timestamp": "2026-01-15T10:30:00.000Z"
    }
  }'

const response = await fetch('https://sandbox.theary.ai/background-check/v1/inbound/notifications', {
  method: 'POST',
  headers: {
    Authorization: 'Bearer YOUR_JWT_TOKEN',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    messageId: 'emp_001',
    threadId: 'thread_abc',
    channel: 'EMAIL',
    messageData: {
      id: 'emp_001',
      threadId: 'thread_abc',
      from: 'hr@techcorp.com',
      to: 'verifications@theary.ai',
      subject: 'Re: Employment Verification - John Doe',
      body: {
        text: 'John Doe was employed as Software Engineer from 2020-01-15 to 2023-12-31. Employee ID: EMP001.',
      },
      timestamp: '2026-01-15T10:30:00.000Z',
    },
  }),
})

const result = await response.json()

import requests

response = requests.post(
    'https://sandbox.theary.ai/background-check/v1/inbound/notifications',
    headers={
        'Authorization': 'Bearer YOUR_JWT_TOKEN',
        'Content-Type': 'application/json'
    },
    json={
        "messageId": "emp_001",
        "threadId": "thread_abc",
        "channel": "EMAIL",
        "messageData": {
            "id": "emp_001",
            "threadId": "thread_abc",
            "from": "hr@techcorp.com",
            "to": "verifications@theary.ai",
            "subject": "Re: Employment Verification - John Doe",
            "body": {
                "text": "Reference: 11111111\n\nJohn Doe was employed as Software Engineer from 2020-01-15 to 2023-12-31. Employee ID: EMP001."
            },
            "timestamp": "2026-01-15T10:30:00.000Z"
        }
    }
)

result = response.json()

Success Response (non-JSON channels): Non-JSON successful submissions return a single root-level employmentVerification object with per-field comparison in fields (not nested in extractedData). Example from an EMAIL channel response for Pablo’s Pizza / John Smith:

{
  "messageId": "emp_001",
  "success": true,
  "classification": {
    "type": "VERIFICATION",
    "confidence": 0.85,
    "reasoning": "Entity verification"
  },
  "extractedData": {
    "outcome": "verified",
    "employerName": "Pablo's Pizza",
    "jobTitle": "Senior Software Developer",
    "startDate": "2022-01-01",
    "endDate": "2023-01-01",
    "extractedApplicantName": "John Smith",
    "verifiedDates": {
      "startDate": "2022-01-01",
      "endDate": "2023-01-01"
    },
    "verifiedContent": {
      "positionTitle": "Senior Software Developer"
    },
    "refId": "EXT-DEV-1781045734449-1",
    "searchType": "EMPLOYMENT"
  },
  "employmentVerification": {
      "fields": {
        "companyName": {
          "type": "string",
          "status": "match",
          "expected": "Pablo's Pizza",
          "extracted": "Pablo's Pizza",
          "comparison": { "engine": "deterministic", "similarity": 1 }
        },
        "position": {
          "type": "string",
          "status": "match",
          "expected": "Senior Software Developer",
          "extracted": "Senior Software Developer",
          "comparison": { "engine": "deterministic", "similarity": 1 }
        },
        "startDate": {
          "type": "date",
          "status": "match",
          "expected": "2022-01-01",
          "extracted": "2022-01-01",
          "comparison": { "engine": "deterministic", "distance": 0 }
        },
        "endDate": {
          "type": "date",
          "status": "match",
          "expected": "2023-01-01",
          "extracted": "2023-01-01",
          "comparison": { "engine": "deterministic", "distance": 0 }
        },
        "applicantName": {
          "type": "string",
          "status": "match",
          "expected": "John Smith",
          "extracted": "John Smith",
          "comparison": { "engine": "deterministic", "similarity": 1 }
        },
        "salary": {
          "type": "number",
          "status": "match",
          "expected": "100000",
          "extracted": "100000",
          "comparison": { "engine": "deterministic", "distance": 0 }
        },
        "location": {
          "type": "string",
          "status": "not_checked",
          "expected": null,
          "extracted": "Grand Junction, CO",
          "comparison": { "engine": "none" }
        },
        "contactNumber": {
          "type": "string",
          "status": "not_checked",
          "expected": null,
          "extracted": "+1-555-200-1000",
          "comparison": { "engine": "none" }
        }
      },
      "doNotContact": false,
      "comments": "Email confirms employment at Pablo's Pizza for John Smith in the stated role and dates."
  },
  "extractedData": {
    "employmentVerified": true,
    "position": "Software Engineer",
    "startDate": "2020-01-15",
    "endDate": "2023-12-31"
  },
  "failureReasons": [],
  "metadata": {
    "contactAnalysis": "ENTITY",
    "searchId": "ae98cdb9-e7b9-4a44-b4e2-d4aa565a2f66",
    "referenceNumbers": ["EXT-DEV-1781045734449-1"],
    "channel": "EMAIL",
    "outcome": "verified"
  },
  "processedAt": "2026-06-09T23:42:32.105Z"
}

Education Form Submission

curl -sS -X POST "https://sandbox.theary.ai/background-check/v1/inbound/notifications" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -d '{
    "messageId": "edu_001",
    "threadId": "thread_xyz",
    "channel": "EFORM",
    "messageData": {
      "id": "edu_001",
      "threadId": "thread_xyz",
      "from": "registrar@university.edu",
      "to": "verifications@theary.ai",
      "subject": "Education Verification - Jane Smith",
      "body": {
        "text": "Reference: 22222222\n\nStudent: Jane Smith\nDegree: BS in Computer Science\nGraduation: 2019-05-15\nGPA: 3.8\nTranscript attached separately via email."
      },
      "timestamp": "2026-01-15T11:45:00.000Z"
    },
    "metadata": {
      "formType": "education_verification"
    }
  }'

Success Response:

{
  "messageId": "edu_001",
  "success": true,
  "classification": {
    "type": "VERIFICATION",
    "confidence": 0.95,
    "reasoning": "Electronic form with structured education verification data"
  },
  "metadata": {
    "searchId": "789e0123-e89b-12d3-a456-426614174002",
    "outcome": "verified"
  },
  "processedAt": "2026-01-15T11:45:03.000Z"
}

Generic JSON Submission

Use channel: "JSON" when an upstream system sends structured third-party verification data instead of an email, fax, or ticket transcript. Place the provider payload in messageData.data. JSON channel requirements:

Field	Required	Notes
`channel`	Yes	Must be `"JSON"`
`messageData.timestamp`	Yes	ISO 8601 timestamp
`messageData.data`	Yes	Non-empty provider payload object
`metadata.searchRefId`	Yes	Search identifier (`externalSearchId` or internal reference)
`messageId`, `threadId`	No	Auto-generated when omitted
`messageData.from`, `messageData.to`	No	Defaults to `metadata.provider` and `"JSON"` for traceability

JSON payloads may contain the full employment or education history returned by the provider. When multiple records are present, SNH AI includes the matched search’s applicant and submitted history context in extraction so the most relevant record can be identified, extracted, and compared to the submitted applicant data.

Supported JSON payload shapes

The API detects employment or education history records from common vendor response layouts. You do not need to normalize the payload to a single schema — pass the vendor object in messageData.data. Employment searches — records are enumerated from:

Path	Typical vendor
`employmentData[]`	Equifax Talent Report Employment Select All (`TrEsaResponse.data`)
`data.employmentData[]`	Wrapped Equifax employment responses
`Data[]`	Thomas & Company Employment Response V2
Other arrays at depth ≤ 2 containing `employer`/`employee`, `Employer`/`Employee`, `Positions`, or `WorkHistories` keys	Fallback detection

Education searches — records are enumerated from:

Path	Typical vendor
`educationVerification.degreeVerification[]`	Equifax Talent Report Education
`educationVerification.enrollmentVerification[]`	Equifax Dates of Attendance
`...degreeVerification[].degreeDetails.degreeDetail[]`	Nested degree records
`...degreeVerification[].enrollmentDetails.enrollmentDetail[]`	Nested enrollment under degree verification
`...enrollmentVerification[].enrollmentDetails.enrollmentDetail[]`	Nested enrollment under enrollment verification
Other arrays at depth ≤ 2 containing `degreeTitle`, `officialNameOfSchool`, `nameOnSchoolRecord`, etc.	Fallback detection

Employment JSON example

curl -sS -X POST "https://sandbox.theary.ai/background-check/v1/inbound/notifications" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -d '{
    "channel": "JSON",
    "messageData": {
      "data": {
        "employmentData": [
          {
            "employer": { "name": "Pablos Pizza" },
            "employee": {
              "firstName": "John",
              "lastName": "Smith",
              "positionTitle": "Senior Software Engineer",
              "mostRecentHireDate": "2022-01-01",
              "terminationDate": "2023-01-01",
              "workLocation": {
                "address": { "city": "Grand Junction", "state": "CO" }
              }
            }
          },
          {
            "employer": { "name": "SNH AI" },
            "employee": {
              "firstName": "John",
              "lastName": "Smith",
              "positionTitle": "Software Engineer",
              "mostRecentHireDate": "2020-01-01",
              "terminationDate": "2023-01-01",
              "workLocation": {
                "address": { "city": "Austin", "state": "TX" }
              }
            }
          },
          {
            "employer": { "name": "Other Corp" },
            "employee": {
              "firstName": "John",
              "lastName": "Smith",
              "positionTitle": "Software Intern",
              "mostRecentHireDate": "2019-01-01",
              "terminationDate": "2020-01-01",
              "workLocation": {
                "address": { "city": "Denver", "state": "CO" }
              }
            }
          }
        ]
      },
      "timestamp": "2026-01-15T12:00:00.000Z"
    },
    "metadata": {
      "provider": "test-provider",
      "searchRefId": "EXT-DEV-1781042158637-1"
    }
  }'

Employment success response: HTTP 200 with the standard processing response body. extractedData contains the best-match scalars and operational flags, while root-level employmentVerification contains the single highest-confidence provider history object.

Education JSON example

curl -sS -X POST "https://sandbox.theary.ai/background-check/v1/inbound/notifications" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "channel": "JSON",
    "messageData": {
      "data": {
        "educationVerification": {
          "degreeVerification": [
            {
              "degreeDetails": {
                "degreeDetail": [
                  {
                    "officialNameOfSchool": "Cape Lookout High School",
                    "degreeTitle": "High School Diploma",
                    "awardDate": "2023-05-15",
                    "nameOnSchoolRecord": {
                      "firstName": "John",
                      "lastName": "Doe"
                    }
                  }
                ]
              }
            }
          ]
        }
      },
      "timestamp": "2024-01-15T12:00:00.000Z"
    },
    "metadata": {
      "provider": "equifax",
      "searchRefId": "EXT-EDU-12345678"
    }
  }'

Successful channel: "JSON" submissions return the same synchronous processing envelope as other channels: messageId, success, classification, extractedData, the applicable root-level employmentVerification / educationVerification object, metadata, and processedAt. The verification object is the highest-confidence provider history row. The employment example selects the row with confidence 0.94 for search EXT-DEV-1781042158637-1. The raw provider payload is not echoed in the synchronous response or webhook payloads. For the full verification.completed JSON closeout shape, see Webhook events — Employment Verification (JSON channel).

Comparison fields: selected JSON record

JSON channel responses expose comparison output at two levels:

Location	Purpose
Root-level `employmentVerification` / `educationVerification` (sync API response, `verification.notification`, activity metadata, `verification.action_required`, `verification.completed`)	Canonical selected verification — the highest-confidence normalized object with per-field `fields..comparison` metadata. Omitted from `extractedData` / `metadata.extractedData`. All externally returned field-level comparison (matches, mismatches, and `match_with_discrepancy`) lives here.*
`extractedData.applicantMismatch`, `_requiresManualReview`	Operational flags (best-match row only) — boolean escalation signals when a critical mismatch triggers manual review. Does not include field-level detail.
`employmentVerification.fields` / `educationVerification.fields`	Selected-row detail — comparison detail for the highest-confidence record. Replaces the removed `applicantMismatches` / `applicantDiscrepancies` objects.

Field comparison metadata (`fields.*.comparison`)

Normalized verification objects (for example employmentVerification.fields on downstream webhooks) attach per-field comparison metadata. similarity is not a universal score — deterministic exact string matches use similarity: 1, and probabilistic / organization-name comparisons use their evaluated score. Date and number fields never include similarity; deterministic matches and mismatches on those types use distance instead.

Field type	Example fields	Match (`status: "match"`)	Mismatch (`status: "mismatch"`)	Discrepancy (`status: "match_with_discrepancy"`)
`date`	`startDate`, `endDate`, `graduationDate`	`comparison.engine`: `deterministic`. `comparison.distance`: calendar days between expected and extracted (`0` for exact dates). No `similarity`.	`comparison.engine`: `deterministic`. `comparison.distance`: calendar days between expected and extracted. No `similarity`.	Not used for dates.
`number`	`salary`, `gpa`	`comparison.engine`: `deterministic`. `comparison.distance`: absolute difference (`0` for exact numbers). No `similarity`.	`comparison.engine`: `deterministic`. `comparison.distance`: absolute difference (for salary, normalized annual USD when both sides parse). No `similarity`.	Not used for numbers.
`string` (LLM semantic / proximity)	`applicantName`, `position`, `degree`, `major`, `location`	Exact normalized match: `comparison.engine`: `deterministic`. `comparison.similarity`: `1`.	`comparison.engine`: `probabilistic` when LLM evaluates the pair. `comparison.similarity`: LLM score (0–1); falls back to `0` when no score is available.	`comparison.engine`: `probabilistic`. `comparison.similarity`: LLM score (0–1).
`string` (organization name)	`companyName`, `schoolName`	Exact normalized match: `comparison.engine`: `deterministic`. `comparison.similarity`: `1`.	May use `probabilistic` LLM fallback or deterministic organization scoring with `similarity`; deterministic mismatches without an evaluated score use `0`.	Typo-tolerant match: `comparison.engine`: `deterministic` or `probabilistic`. May include `comparison.similarity` from string-similarity or LLM scoring.

Examples Location proximity mismatch:

"location": {
  "type": "string",
  "status": "mismatch",
  "expected": "Grand Junction, CO",
  "extracted": "Austin, TX",
  "reason": "The locations are in different states and are not geographically close.",
  "comparison": { "engine": "probabilistic", "similarity": 0.1 }
}

Location proximity discrepancy:

"location": {
  "type": "string",
  "status": "match_with_discrepancy",
  "expected": "Phoenix, AZ",
  "extracted": "Scottsdale, AZ",
  "reason": "The locations are highly similar because Scottsdale is in the Phoenix metro area.",
  "comparison": { "engine": "probabilistic", "similarity": 0.95 }
}

Deterministic date match (distance: 0, no similarity):

"startDate": {
  "type": "date",
  "status": "match",
  "expected": "2022-01-01",
  "extracted": "2022-01-01",
  "reason": "exact match",
  "comparison": { "engine": "deterministic", "distance": 0 }
}

LLM semantic discrepancy (similarity present):

"position": {
  "type": "string",
  "status": "match_with_discrepancy",
  "expected": "Senior Software Developer",
  "extracted": "Senior Software Engineer",
  "reason": "Software Developer and Software Engineer describe the same engineering function.",
  "comparison": { "engine": "probabilistic", "similarity": 0.98 }
}

Downstream webhook delivery

In addition to the synchronous response body, successful JSON submissions emit extraction and the selected normalized verification object asynchronously. Primary delivery paths:

verification.notification with notificationType: "INBOUND_RECEIVED_DETAIL" — best-match scalars (and optional applicantMismatch / _requiresManualReview flags) at data.metadata.extractedData; the highest-confidence record with per-field comparison at root-level data.employmentVerification or data.educationVerification (not nested in extractedData). applicantMismatches and applicantDiscrepancies are not included.
verification.action_required with reasonCode: "HUMAN_ESCALATION" or "OTHER" — when manual review is required for non-verified or JSON-channel holds; extractedData under data.metadata.extractedData without duplicate verification data. JSON-channel only (channel: "JSON", status: "QA Review"): root-level data.message (human-readable review summary for client UI) plus the highest-confidence data.employmentVerification or data.educationVerification object. EMAIL/FAX/VOICE action-required webhooks omit message. Verified EMAIL/FAX/VOICE with field mismatches typically close via verification.completed and verificationResult.discrepancy: true instead.
Activity metadata — root-level employmentVerification / educationVerification plus stripped extractedData (same split as webhooks), alongside messageId, threadId, contactType, and messageContext
verification.completed — root-level data.employmentVerification (or data.educationVerification) as the single highest-confidence object for JSON. data.verificationResult.extractedData keeps scalar extraction and comparison metadata without duplicate verification data. verificationResult.discrepancy is the operational closeout flag and may be false when the selected row only has non-critical fields.*.status: "match_with_discrepancy" entries.

The examples below show the INBOUND_RECEIVED_DETAIL webhook envelope for search 86bc0a43-6a10-4f85-a093-e4244ed78107 / EXT-DEV-1781042158637-1 (Pablo’s Pizza / John Smith). metadata.extractedData is identical wherever that object appears; the selected verification object sits at the payload root.

{
  "event": "verification.notification",
  "occurredAt": "2026-06-09T22:00:00.000Z",
  "data": {
    "searchId": "86bc0a43-6a10-4f85-a093-e4244ed78107",
    "externalSearchId": "EXT-DEV-1781042158637-1",
    "searchType": "EMPLOYMENT",
    "notificationType": "INBOUND_RECEIVED_DETAIL",
    "from": "test-provider",
    "classification": {
      "type": "VERIFICATION",
      "confidence": 0.94
    },
    "employmentVerification": {
        "confidence": 0.94,
        "fields": {
          "companyName": {
            "type": "string",
            "status": "match",
            "expected": "Pablo's Pizza",
            "extracted": "Pablos Pizza",
            "comparison": { "engine": "deterministic", "similarity": 1 }
          },
          "position": {
            "type": "string",
            "status": "match_with_discrepancy",
            "expected": "Senior Software Developer",
            "extracted": "Senior Software Engineer",
            "comparison": { "engine": "probabilistic", "similarity": 0.98 }
          },
          "startDate": {
            "type": "date",
            "status": "mismatch",
            "expected": "2022-01-01",
            "extracted": "2021-01-01",
            "comparison": { "engine": "deterministic", "distance": 365 }
          },
          "endDate": {
            "type": "date",
            "status": "match",
            "expected": "2023-01-01",
            "extracted": "2023-01-01",
            "comparison": { "engine": "deterministic", "distance": 0 }
          },
          "location": {
            "type": "string",
            "status": "match",
            "expected": "Grand Junction, CO",
            "extracted": "Grand Junction, CO",
            "comparison": { "engine": "deterministic", "similarity": 1 }
          },
          "applicantName": {
            "type": "string",
            "status": "match",
            "expected": "John Smith",
            "extracted": "John Smith",
            "comparison": { "engine": "deterministic", "similarity": 1 }
          }
      }
    },
    "metadata": {
      "source": "inbound",
      "channel": "JSON",
      "timestamp": "2026-06-09T22:00:00.000Z",
      "to": "JSON",
      "upstreamProvider": "test-provider",
      "extractedData": {
        "outcome": "verified",
        "refId": "EXT-DEV-1781042158637-1",
        "searchType": "EMPLOYMENT",
        "employerName": "Pablos Pizza",
        "jobTitle": "Senior Software Engineer",
        "startDate": "2021-01-01",
        "endDate": "2023-01-01",
        "employerLocation": "Grand Junction, CO",
        "extractedApplicantName": "John Smith",
        "_processedFromJson": true,
        "_thirdPartyProvider": "test-provider",
        "applicantMismatch": true,
        "_requiresManualReview": true
      }
    }
  }
}

{
  "event": "verification.notification",
  "occurredAt": "2026-06-09T22:00:00.000Z",
  "data": {
    "searchId": "86bc0a43-6a10-4f85-a093-e4244ed78107",
    "externalSearchId": "EXT-DEV-1781042158637-1",
    "searchType": "EMPLOYMENT",
    "notificationType": "INBOUND_RECEIVED_DETAIL",
    "from": "test-provider",
    "classification": { "type": "VERIFICATION", "confidence": 0.94 },
    "employmentVerification": {
        "confidence": 0.94,
        "fields": {
          "companyName": {
            "type": "string",
            "status": "match",
            "expected": "Pablo's Pizza",
            "extracted": "Pablos Pizza",
            "comparison": { "engine": "deterministic", "similarity": 1 }
          },
          "position": {
            "type": "string",
            "status": "match_with_discrepancy",
            "expected": "Senior Software Developer",
            "extracted": "Senior Software Engineer",
            "comparison": { "engine": "probabilistic", "similarity": 0.98 }
          },
          "startDate": {
            "type": "date",
            "status": "match",
            "expected": "2022-01-01",
            "extracted": "2022-01-01",
            "comparison": { "engine": "deterministic", "distance": 0 }
          },
          "endDate": {
            "type": "date",
            "status": "match",
            "expected": "2023-01-01",
            "extracted": "2023-01-01",
            "comparison": { "engine": "deterministic", "distance": 0 }
          },
          "location": {
            "type": "string",
            "status": "match",
            "expected": "Grand Junction, CO",
            "extracted": "Grand Junction, CO",
            "comparison": { "engine": "deterministic", "similarity": 1 }
          },
          "applicantName": {
            "type": "string",
            "status": "match",
            "expected": "John Smith",
            "extracted": "John Smith",
            "comparison": { "engine": "deterministic", "similarity": 1 }
          }
      }
    },
    "metadata": {
      "source": "inbound",
      "channel": "JSON",
      "timestamp": "2026-06-09T22:00:00.000Z",
      "to": "JSON",
      "upstreamProvider": "test-provider",
      "extractedData": {
        "outcome": "verified",
        "refId": "EXT-DEV-1781042158637-1",
        "searchType": "EMPLOYMENT",
        "employerName": "Pablos Pizza",
        "jobTitle": "Senior Software Engineer",
        "startDate": "2022-01-01",
        "endDate": "2023-01-01",
        "employerLocation": "Grand Junction, CO",
        "extractedApplicantName": "John Smith",
        "_processedFromJson": true,
        "_thirdPartyProvider": "test-provider"
      }
    }
  }
}

Note: For JSON, root-level employmentVerification / educationVerification is the highest-confidence object. Field-level comparison for that selected row appears on data.employmentVerification.fields / data.educationVerification.fields. applicantMismatches and applicantDiscrepancies are not included in webhook or inbound notification payloads — use fields.* instead. When a critical mismatch triggers escalation, metadata.extractedData may include applicantMismatch: true and _requiresManualReview: true without field-level objects. When the search closes without escalation, verification.completed may set verificationResult.discrepancy: false even though employmentVerification.fields.position.status is match_with_discrepancy — see Webhook events.

Auto-Generated IDs

When messageId or threadId are not provided, the system automatically generates them:

curl -sS -X POST "https://sandbox.theary.ai/background-check/v1/inbound/notifications" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -d '{
    "channel": "EMAIL",
    "messageData": {
      "from": "hr@company.com",
      "to": "verifications@theary.ai",
      "subject": "Employment Verification - John Doe",
      "body": {
        "text": "Reference: 11111111\n\nJohn Doe worked here from 2020-01-15 to 2023-12-31 as Software Engineer."
      },
      "timestamp": "2026-01-15T10:30:00.000Z"
    }
  }'

Note: The system will automatically generate messageId and threadId if not provided. The generated IDs will be returned in the response.

Error Responses

This endpoint always returns HTTP 200 (the controller forces @HttpCode(HttpStatus.OK)), even when processing fails. Failures are represented in the response body, not the HTTP status — check the success and failureReasons fields on every response.

{
  "messageId": "msg_001",
  "success": false,
  "failureReasons": ["metadata.searchRefId is required for JSON channel requests"],
  "processedAt": "2024-01-15T10:30:00.000Z"
}

{
  "messageId": "msg_001",
  "success": false,
  "failureReasons": ["No JSON payload found"],
  "processedAt": "2024-01-15T10:30:00.000Z"
}

{
  "messageId": "msg_001",
  "success": false,
  "failureReasons": ["Search EXT-DEV-1781042158637-1 not found in verification system"],
  "processedAt": "2024-01-15T10:30:00.000Z"
}

{
  "messageId": "msg_001",
  "success": false,
  "failureReasons": ["Search not found"],
  "processedAt": "2024-01-15T10:30:00.000Z"
}

{
  "statusCode": 400,
  "message": "messageData.from, messageData.to required for EMAIL channel",
  "error": "Bad Request"
}

{
  "statusCode": 401,
  "message": "Unauthorized"
}

{
  "statusCode": 400,
  "message": ["messageData.timestamp should not be empty", "channel must be a valid enum value"],
  "error": "Bad Request"
}

Validation failures on this request return the same generic 400 Bad Request shape as every other endpoint — there is no 422 status configured for this API. messageId is optional and can never trigger a “should not be empty” failure; messageData.timestamp is the field actually marked as required.

{
  "statusCode": 400,
  "message": "messageData.from, messageData.to required for EMAIL channel",
  "error": "Bad Request"
}

Non-JSON channels also require messageData.from and messageData.to; the controller checks this explicitly and returns a single-string 400 message (not the array shape) naming the missing fields.

How It Works

The inbound notification processing follows these steps:

Submit - You send verification response via API
ID Generation - If messageId or threadId are not provided, they are auto-generated
Validate - System validates required fields and checks for malicious content. For JSON channel, validates that metadata.searchRefId and a non-empty messageData.data payload are present. For other channels, validates messageData.from and messageData.to.
Match - Links message to active verification search:
- JSON channel: Matches exclusively on metadata.searchRefId (external search ID or internal reference). Does not scan the payload body for reference numbers.
- Other channels: Extracts 7–8 digit reference numbers from subject, body, attachments, or uses metadata.searchRefId / threadId when provided.
Process Attachments - PDF attachments are processed to extract text content (if present; skipped for JSON channel)
Analyze Contact - Determines sender type (APPLICANT, ENTITY, or UNKNOWN). JSON channel requests are treated as ENTITY responses.
Classify & Extract - AI-powered classification extracts verification details:
- JSON channel: Extracts directly from structured provider payload; selects the best-matching employment or education record when multiple are present.
- Other channels: Analyzes the message content to extract structured verification data.
- Extracts structured outcome (VERIFIED, NO_RECORD, THIRD_PARTY, INFO_REQUESTED, etc.)
- Parses verification data (dates, positions, confirmation status)
Cross-check Provided Data - Compares extracted applicant, employment, or education details against the order data on file. Tenant comparison settings (see tenant config.comparisonConfig) tune behavior: calendar-day windows per date field (startDate, endDate, graduationDate), semantic equivalence thresholds for applicant name, job title, degree, major, and location proximity, and salary tolerances. For employment salary, when both the order value (providedSalary in search metadata) and the extracted salary parse, the API normalizes common compensation text (for example annual, hourly, monthly, weekly, and k / m suffixes) to an estimated annual USD amount and treats a mismatch only if the gap exceeds both the configured absolute-dollar threshold and the relative (percent) threshold; otherwise it falls back to the same normalized string comparison used for other plain-text fields. Mismatch reasons for dates and salaries include the compared raw values (and annualized figures for salary) to aid review.
Persist Results - Saves processing results, classification, and extracted data
Update Search - Updates search status if terminal outcome (VERIFIED, NO_RECORD, THIRD_PARTY, WRONG_ORG)
Schedule Follow-up - If non-terminal outcome (INFO_REQUESTED, INSUFFICIENT), schedules next outbound attempt
Notify - Sends webhook if verification reaches terminal state

Common Use Cases

Use Case	Channel	Best For
Email from HR	`EMAIL`	Employment verification responses
University form	`EFORM`	Education verification with transcripts
Fax response	`FAX_WEBHOOK`	Legacy systems, healthcare, legal
Office 365	`MICROSOFT_GRAPH`	Enterprise email automation
Help desk	`TICKETING`	Support ticket workflows
Generic JSON	`JSON`	Structured third-party provider payloads

Best Practices

Message IDs:

Use unique identifiers (UUIDs recommended) if available
Never reuse message IDs
Optional: Omit the field entirely if you don’t have one - the system will auto-generate it
If provided, ensure it’s unique across all messages

Thread IDs:

Keep consistent for related messages in the same conversation thread
Helps track conversation history across multiple exchanges
Optional: Omit the field entirely if you don’t have one - the system will use the messageId as the threadId
Use the same threadId for all messages in the same conversation

Timestamps:

Always use ISO 8601 format
Example: 2026-01-15T10:30:00.000Z

Content (email, fax, form, ticketing channels):

Include all verification details in the body.text field
Include reference number: The message must contain a 7-8 digit reference number to match the message to the correct verification search. The system looks for patterns like:
- “Reference: 12345678”
- “Ref. 12345678”
- “Ticket # 12345678”
- “Case # 12345678”
- Or standalone 7-8 digit numbers
Mention attachments sent via separate channels if needed

Content (JSON channel):

Set channel to "JSON" and place the vendor response in messageData.data
Always include metadata.searchRefId — this is the only search-matching mechanism for JSON requests. Use the search’s external ID (e.g. EXT-DEV-1781042158637-1) or internal reference number
Set metadata.provider to identify the upstream system for audit and traceability
Pass the vendor payload as-is; normalization to a single schema is not required
When the provider returns multiple employment or education records, include all of them — the API selects the record that best matches the applicant and submitted search data

Error Handling:

For every channel, HTTP 200 includes a response body; check success and process failureReasons when present
Successful responses include best-match scalars in extractedData and the highest-confidence normalized provider record in the applicable root-level verification object
Implement retry with exponential backoff for server errors

Troubleshooting

“metadata.searchRefId is required for JSON channel requests”

Include metadata.searchRefId on every channel: "JSON" request
The value must be a non-empty string

“No JSON payload found”

Ensure messageData.data is a non-empty object containing at least one enumerable employment or education record
Do not send only { "text": "..." } or { "html": "..." } keys without structured verification data

“Search not found in verification system” (JSON channel)

Verify metadata.searchRefId matches the search’s externalSearchId or internal reference
Ensure the search is still active (not completed or cancelled)
Check that the search has the INBOUND objective enabled

“Search not found” (non-JSON channels)

Verify the message contains a valid 7-8 digit reference number in one of the supported formats:
- “Reference: 12345678”
- “Ref. 12345678”
- “Ticket # 12345678”
- “Case # 12345678”
- Or a standalone 7-8 digit number
Ensure the reference number matches an active verification search
Ensure search is still active (not completed or cancelled)
Check that the search has the INBOUND objective enabled
Check sender email matches expected contact (if applicable)

“messageData.from, messageData.to required for channel”

Non-JSON channels require both messageData.from and messageData.to
These fields are optional only when channel is "JSON"

“Invalid message format”

All required fields must be present for the channel type
Check timestamp is valid ISO 8601

“Validation error”

Review error messages in response
Verify data types match requirements
Ensure all required fields are present

Next Steps

Authorizations

Authorization

string

header

required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json

messageData

Message Data · object

required

Message data

Show child attributes

messageId

string

Message ID to process (auto-generated if not provided)

threadId

string

Thread ID (auto-generated if not provided)

channel

enum<string>

Channel type

Available options:

MICROSOFT_GRAPH,

FAX_WEBHOOK,

STANDARD,

EMAIL,

TICKETING,

JITBIT,

EFORM

metadata

object

Additional metadata. Can include pre-extracted data from upstream systems: - provider: Source system identifier (e.g., 'SNH AI ', 'JITBIT') - searchRefId: Reference ID for the search - activityId: Activity ID from upstream system - link: URL to original ticket/message - intention: Pre-classified intent (VERIFICATION, INFO_REQUEST, THIRD_PARTY, etc.) - confidence: Confidence level from upstream (0-1). Defaults to 0.95 if not provided. - structuredData: Pre-extracted verification data with verifiedInfo and verificationResult

When structuredData is provided with verifiedInfo, the system will use this
pre-extracted data instead of re-processing, improving accuracy and efficiency.

Supported verificationResult values: VERIFIED, VERIFIED_DISCREPANCY, VERIFIED_NO_DISCREPANCY,
UNABLE_TO_VERIFY, UNVERIFIED, NO_RECORD, RECORD_NOT_FOUND, THIRD_PARTY, WRONG_ENTITY

Example:

{
  "provider": "UPSTREAM_SYSTEM",
  "searchRefId": "12345678",
  "intention": "VERIFICATION",
  "confidence": 0.95,
  "structuredData": {
    "verifiedInfo": {
      "subjectName": "John Smith",
      "employerName": "Tech Corp",
      "startDate": "2020-01-15",
      "endDate": "2023-06-30",
      "position": "Software Engineer"
    },
    "verificationResult": "VERIFIED"
  }
}

Response

200 - application/json

The response is of type object.

Create Batch Order Generate Upload URL

Overview

Orders API

Search Management

Batches API

Inbound API

Files API

Closeout Events API

Request and order schemas

Webhook schemas

Submit Inbound Notification

Submit Inbound Notification

Authentication

Quick Examples

Request Parameters

Optional Fields

Optional Fields

Attachments

Response

Classification Types

Examples

Employment Verification

Education Form Submission

Generic JSON Submission

Supported JSON payload shapes

Employment JSON example

Education JSON example

Comparison fields: selected JSON record

Field comparison metadata (`fields.*.comparison`)

Downstream webhook delivery

Auto-Generated IDs

Error Responses

How It Works

Common Use Cases

Best Practices

Troubleshooting

Next Steps

Authorizations

Body

Response

​Submit Inbound Notification

​Authentication

​Quick Examples

​Request Parameters

​Optional Fields

​Optional Fields

​Attachments

​Response

​Classification Types

​Examples

​Employment Verification

​Education Form Submission

​Generic JSON Submission

​Supported JSON payload shapes

​Employment JSON example

​Education JSON example

​Comparison fields: selected JSON record

​Field comparison metadata (fields.*.comparison)

​Downstream webhook delivery

​Auto-Generated IDs

​Error Responses

​How It Works

​Common Use Cases

​Best Practices

​Troubleshooting

​Next Steps

Authorizations

Body

Response

Submit Inbound Notification

Authentication

Quick Examples

Request Parameters

Optional Fields

Optional Fields

Attachments

Response

Classification Types

Examples

Employment Verification

Education Form Submission

Generic JSON Submission

Supported JSON payload shapes

Employment JSON example

Education JSON example

Comparison fields: selected JSON record

Field comparison metadata (`fields.*.comparison`)

Downstream webhook delivery

Auto-Generated IDs

Error Responses

How It Works

Common Use Cases

Best Practices

Troubleshooting

Next Steps