Automate customer onboarding verification

One of the earliest and most well defined use cases of Deep Learning has been face identification and verification. Arya's face recognition module is one of the robust modules trained to recognise and match faces from a variety of sources such as surveillance footage or images.

    Cutting-Edge Features    

Why Arya Face Verification?

Identity and Image Fraud Minimization

Minimize identity theft and image fraud risks effectively.

Face Recognition Across Sources

Recognise and match faces from various sources accurately

10 M+ Monthly Verifications

Performed over 10 million verifications monthly

<1 Minute Verification Time

Complete verifications in less than a minute

An AI Platform that you've
always wanted
With more than 80+ APIs, we stand out as the go-to-platform for developers, consistently delivering unparalleled success rates in driving critical decisions.
200 M+

Annual API Volume

95 %+

Accuracy Rate

720 K

Daily API Volume

< 5 Mins

Time to launch

    Effortless AI For Everyone    

More Reasons To Love Arya AI

Hassle-Free,

No Code Platform

Easy to adopt

& integrate

99.99%

API Success Rate

Reliable &

Secure

    Helpful Resources    

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Sample 1 to compare

Please select sample images from each section and click SUBMIT to test the api.

Sample 2 to compare

Please select sample images from each section and click SUBMIT to test the api.

Drag and drop files

Supports: PDF, JPG, PNG, etc

Drag and drop files

Supports: PDF, JPG, PNG, etc

Drag and drop files

Supports: PDF, JPG, PNG, etc

Faces Matched!

Matching Score: {{outputSample.score || output.score |percent}}%

Faces Not Matched!

Matching Score: {{outputSample.score || output.score |percent}}%

Documentation

HTTP Method: Post
Endpoint
{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}
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API Token
{{tokenDisplay}}
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API Token UAT
postman wrapper button
{{tokenUDisplay}}
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Usage and Code Samples

curl --location --request POST '{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}' \
--header 'token: < your private token >' \
--header 'content-type: application/json' \
--data-raw '{
	"doc1_type":'image',
	"doc2_type":'image',
	"img1_base64": '< base64 string of document >',
	"img2_base64": '< base64 string of document >',
	"req_id": '< req id string >'
	     }'
OkHttpClient client = new OkHttpClient().newBuilder().build();
MediaType mediaType = MediaType.parse("application/javascript");
RequestBody body = RequestBody.create(mediaType, "{ "doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >'  }");
Request request = new Request.Builder()
	.url("{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}")
	.method("POST", body)
	.addHeader("token", "< your private token >")
	.addHeader("content-type", "application/json")
	.build();
Response response = client.newCall(request).execute();
require "uri"
require "net/http"
url = URI("{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}")
https = Net::HTTP.new(url.host, url.port)
https.use_ssl = true
request = Net::HTTP::Post.new(url)
request["token"] = "< your private token >"
request["content-type"] = "application/json"
request.body = "{"doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >'  }"
response = https.request(request)
puts response.read_body
CURL *curl;
CURLcode res;
curl = curl_easy_init();
if(curl) {
  curl_easy_setopt(curl, CURLOPT_CUSTOMREQUEST, "POST");
  curl_easy_setopt(curl, CURLOPT_URL, "{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}");
  curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L);
  curl_easy_setopt(curl, CURLOPT_DEFAULT_PROTOCOL, "https");
  struct curl_slist *headers = NULL;
  headers = curl_slist_append(headers, "token: < your private token >");
  headers = curl_slist_append(headers, "content-type: application/json");
  curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);
  const char *data = "{"doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >'  }";
  curl_easy_setopt(curl, CURLOPT_POSTFIELDS, data);
  res = curl_easy_perform(curl);
}
curl_easy_cleanup(curl);
var request = require('request');
var options = {
  'method': 'POST',
  'url': '{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}',
  'headers': {
  'token': '< your private token >',
  'content-type':'application/json'
},
body: '{"doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >'  }'
};
request(options, function (error, response) {
if (error) throw new Error(error);
  console.log(response.body);
});
var client = new RestClient("{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}");
ṣclient.Timeout = -1;
var request = new RestRequest(Method.POST);
request.AddHeader("token", "< your private token >");
request.AddHeader("content-type", "application/json");
var body = @"{" + "" +
@"    "doc1_type": 'image'," + "" +
@"    "img1_base64": '< base64 string of document >'," + "" +
@"    "doc2_type": 'image'," + "" +
@"    "img2_base64": '< base64 string of document >'," + "" +
@"    "req_id": < req id string >" + "" +
@"  }";
request.AddParameter("application/json", body,  ParameterType.RequestBody);
IRestResponse response = client.Execute(request);
Console.WriteLine(response.Content);
php
require_once 'HTTP/Request2.php';
$request = new HTTP_Request2();
$request->setUrl('{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}');
$request->setMethod(HTTP_Request2::METHOD_POST);
$request->setConfig(array(
'follow_redirects' => TRUE
));
$request->setHeader(array(
  'token' => '< your private token >',
  'content-type' => 'application/json'
));
$request->setBody('{"doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >'  }');
try {
  $response = $request->send();
  if ($response->getStatus() == 200) {
  echo $response->getBody();
  }
  else {
  echo 'Unexpected HTTP status: ' . $response->getStatus() . ' ' .
  $response->getReasonPhrase();
  }
}
catch(HTTP_Request2_Exception $e) {
  echo 'Error: ' . $e->getMessage();
}
?>
import requests
url = "{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}"
payload = {"doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >'  }
headers = {
  'token': '< your private token >',
  'content-type':'application/json'
}
response = requests.request("POST", url, json=payload, headers=headers)
print(response.text)

Request Parameters

Header parameters
Name Description
token String
Body parameters
Name Description
body {
  "req_id" : < string >,
  "doc_base64": < base64 encoded string >
  "doc_type" : < string>,
}

Response Parameters

Status: 200 - API Request Successful
Body parameters
Name Description
body {
  "req_id" : < string >,
  "success" : < boolean >,
  "doc_type": < string >,
  "error_message" : < string >,
  "data" : < dict >,
}

Field Details

Request Field Details
Fields Values/Description
doc_type “image" / "pdf”
req_id Unique request ID used for processing requests
doc_base64 Base64 encoded string of the document
Response Field Details
Fields Values/Description
req_id Corresponding request id
success Flag if the request is processed successfully
doc_type Type of document uploaded
error_message If success is False then: Error message
data Dictionary of extracted data