Verify Face (1:1 vs enrolled person)

Endpoint

POST https://api.verifik.co/v2/face-recognition/verify

Verifies that one or more probe face images match a specific enrolled person identified by id (MongoDB person _id). Returns the enrolled profile and a similarity score when the match meets min_score. Use optional collection_id to scope the check.

Headers

Name	Value
Content-Type	application/json
Authorization	Bearer <token>

Params

Name	Type	Required	Description
id	string	Yes	MongoDB _id of the enrolled person to verify against.
images	string[]	Yes	Base64 face images (raw base64; same subject as the enrolled person).
min_score	number	Yes	Match threshold between 0.5 and 1.
search_mode	string	Yes	FAST or ACCURATE.
collection_id	string	No	Optional scope when the person belongs to multiple collections.

Request

Node.js

const fetch = require("node-fetch");

const personId = "68defec6a9a7b4933d5652f3";

async function run() {
  const res = await fetch("https://api.verifik.co/v2/face-recognition/verify", {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      Authorization: `Bearer ${process.env.VERIFIK_TOKEN}`,
    },
    body: JSON.stringify({
      id: personId,
      images: ["<base64>", "<base64>"],
      min_score: 0.75,
      search_mode: "FAST",
      collection_id: "<optional_collection_mongo_id>",
    }),
  });
  console.log(await res.json());
}

run();

PHP

<?php
$personId = "68defec6a9a7b4933d5652f3";
$ch = curl_init("https://api.verifik.co/v2/face-recognition/verify");
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Content-Type: application/json",
    "Authorization: Bearer " . getenv("VERIFIK_TOKEN")
]);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode([
    "id" => $personId,
    "images" => ["<base64>", "<base64>"],
    "min_score" => 0.75,
    "search_mode" => "FAST",
    "collection_id" => "<optional_collection_mongo_id>",
]));
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
$response = curl_exec($ch);
curl_close($ch);
echo $response;

Python

import os, requests

person_id = "68defec6a9a7b4933d5652f3"
url = "https://api.verifik.co/v2/face-recognition/verify"
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {os.getenv('VERIFIK_TOKEN')}",
}
payload = {
    "id": person_id,
    "images": ["<base64>", "<base64>"],
    "min_score": 0.75,
    "search_mode": "FAST",
    "collection_id": "<optional_collection_mongo_id>",
}
r = requests.post(url, json=payload, headers=headers)
print(r.json())

Go

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "net/http"
    "os"
)

func main() {
    personId := "68defec6a9a7b4933d5652f3"
    payload, _ := json.Marshal(map[string]interface{}{
        "id":             personId,
        "images":         []string{"<base64>", "<base64>"},
        "min_score":      0.75,
        "search_mode":    "FAST",
        "collection_id":  "<optional_collection_mongo_id>",
    })
    req, _ := http.NewRequest("POST", "https://api.verifik.co/v2/face-recognition/verify", bytes.NewReader(payload))
    req.Header.Set("Content-Type", "application/json")
    req.Header.Set("Authorization", "Bearer "+os.Getenv("VERIFIK_TOKEN"))
    resp, _ := http.DefaultClient.Do(req)
    defer resp.Body.Close()
    var out map[string]interface{}
    json.NewDecoder(resp.Body).Decode(&out)
    fmt.Println(out)
}

Response

200

{
  "id": "9DVKW",
  "data": {
    "match": {
      "id": "68defec6a9a7b4933d5652f3",
      "name": "Jane Doe",
      "score": 0.9132,
      "gender": "F",
      "date_of_birth": "1990-01-15",
      "thumbnails": [
        { "id": "thumb-uuid", "thumbnail": "<base64>" }
      ],
      "collections": []
    }
  },
  "signature": {
    "message": "Certified by Verifik.co",
    "dateTime": "April 9, 2026 12:12 AM"
  }
}

401

{
  "message": "Authentication required",
  "code": "UNAUTHORIZED"
}

403

{
  "message": "token_expired",
  "code": "FORBIDDEN"
}

409

{
  "message": "\"min_score\" is required",
  "code": "MissingParameter"
}

500

{
  "message": "internal_error",
  "code": "ERROR"
}

Notes

• 1:1 vs enrollment: Unlike Face Search (1:N), you already know which person to test; this endpoint scores probe images against that record.
• Images: Use one or more captures of the same subject; raw base64 without a data: prefix unless your client adds it consistently.
• Related flows: For comparing two arbitrary image sets without an enrolled id, use Face Comparison; for gallery search, use Face Search.