Next-gen AI-Powered OCR Platform
Efficient, Accurate, and Secure
AI Data Extraction
Data extraction made easy with AI-powered OCR through a no-code platform or API integration.
Extract faster with 99% accuracy while saving cost.
See how Valitract works
Powerful OCR with
AI-Based Data Extraction
Smart data extraction
Leverage AI-powered smart data extraction to effortlessly handle unformatted documents. Our fully automated system handles everything, from parsing and validating to extracting data accurately with up to 99.8% precision.
“Process 1000 of our PDF files within seconds and without any errors. Simply amazing solution all around.”
Jamie Lynn | Account Executive
Customizable data fields & labels
Simplify document extraction with customizable data fields and labels tailored to your needs. Whether you want us to handle the entire extraction process or select specific fields, we’ve got you covered.
“The ready-to-use template is great! Appreciate the flexibility for labels and data fields.”
Steve Bricks | Operation Manager
Any Doc, Any Language
Effortlessly extract data from images and documents in any language. Our OCR system supports over 95 languages and processes various input types, including PDFs, images, screenshots, scans, and more, making it ideal for global businesses
“It’s amazing. They actually can read our data from all type of forms.”
Jacob Petterson | HR Director
Ready-to-use data output
Receive extracted data in structured formats such as JSON, XLS, or CSV, ready for seamless integration with databases, analytics tools, or other applications.
“Super happy with the output options. Save us tons of time since we can send the pulled data to our CRM, ERP, as well as our database directly. This is true automation. ”
Rose | COO
No-code Platform
Interact with our solution effortlessly through simple clicks. No coding or complex configurations required unless you want to.
“I’ve been an accountant for 30 years and this app has help me out immensely. I don’t understand fully how they do it but it only takes a few set up to have the results I want.”
Amber Taylor| Account Executive
AI-Powered OCR: Accurate, Flexible, and Secure
Document Processing That Actually Works
Industry-leading accuracy on complex documents, or we’ll credit your next batch. Built to handle your most challenging formats.
Benny Wilson
Mid-Market
(51-1000 emp.)
Great tools, even better service. Take me 5 minutes to set up and we’re more than happy with the results.
Simple, Flexible Plans
Flexible monthly plans with clear volume tiers. Choose what fits your needs, from Start to Enterprise scale.
Lucas I
Small-Business
(50 or fewer emp.)
Best of class OCR with great price. We could’ve spent a fortune on extracting the holiday sales invoice.
Your Data Stays Confidential, Always
Enterprise-level security protocols. Automatic data purge. Your data is never used to train our models.
Selena
Enterprise (>1000 emp.)
The app is super upfront about their data confidentiality policy. We don’t need to worry that our private information of customers floating around the Internet since the app deletes them immediately!
Intelligent OCR for All Document Types
Say goodbye to manual entry! Valitract transforms any document types into valuable and actionable data.
Invoices
Capture vendor details, line items, totals, and payment terms from any invoice format
Receipt
Extract merchant, itemized purchases, and transaction dates from any receipt, even the handwritten
Bank Statement
Extract transactions, account details, and balances from any bank statement format
Passport
Read MRZ codes, personal details, and expiry dates instantly, remove manual entry from your KYC
Resume / CV
Pull contact details, work history, skills, and education straight into your ATS or HR database automatically
ID Card
Capture names, ID numbers, and dates of birth from national ID cards across formats and countries
The easiest AI-powered OCR API to use
Once you sign up with a business email, click on My Account > API Keys to get your key.
This key will allow you to authenticate API requests.
import java.io.*;
import java.net.*;
import org.json.*;
public class ValitractOCR {
private static final String API_KEY = "your_api_key_here";
private static final String API_URL = "https://api.valitract.com/api/v1/extract-generic";
public static void main(String[] args) {
try {
File file = new File("document.pdf");
String result = processOCR(file);
System.out.println("Extracted Data: " + result);
} catch (Exception e) {
e.printStackTrace();
}
}
public static String processOCR(File file) throws Exception {
HttpURLConnection conn = (HttpURLConnection) new URL(API_URL).openConnection();
conn.setRequestMethod("POST");
conn.setRequestProperty("Authorization", "Bearer " + API_KEY);
conn.setDoOutput(true);
// Upload file and get response
return "JSON Response";
}
}package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"mime/multipart"
"net/http"
"os"
)
const (
apiKey = "your_api_key_here"
apiURL = "https://api.valitract.com/api/v1/extract-generic"
)
type OCRResponse struct {
FileName string `json:"file_name"`
ExtractedData map[string]interface{} `json:"extracted_data"`
}
func processOCR(filePath string) (*OCRResponse, error) {
file, err := os.Open(filePath)
if err != nil {
return nil, err
}
defer file.Close()
body := &bytes.Buffer{}
writer := multipart.NewWriter(body)
part, _ := writer.CreateFormFile("file", filePath)
io.Copy(part, file)
writer.Close()
req, _ := http.NewRequest("POST", apiURL, body)
req.Header.Set("Authorization", "Bearer "+apiKey)
req.Header.Set("Content-Type", writer.FormDataContentType())
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
return nil, err
}
defer resp.Body.Close()
var result OCRResponse
json.NewDecoder(resp.Body).Decode(&result)
return &result, nil
}
func main() {
result, err := processOCR("document.pdf")
if err != nil {
fmt.Println("Error:", err)
return
}
fmt.Printf("Extracted Data: %+v\n", result)
}const axios = require('axios');
const FormData = require('form-data');
const fs = require('fs');
const API_KEY = 'your_api_key_here';
const API_URL = 'https://api.valitract.com/api/v1/extract-generic';
async function processOCR(filePath) {
try {
const form = new FormData();
form.append('file', fs.createReadStream(filePath));
const response = await axios.post(API_URL, form, {
headers: {
'Authorization': `Bearer ${API_KEY}`,
...form.getHeaders()
}
});
console.log('Extracted Data:', response.data);
return response.data;
} catch (error) {
console.error('Error processing OCR:', error.message);
throw error;
}
}
// Usage
processOCR('document.pdf')
.then(data => console.log('Success:', data))
.catch(err => console.error('Failed:', err));<?php
define('API_KEY', 'your_api_key_here');
define('API_URL', 'https://api.valitract.com/api/v1/extract-generic');
function processOCR($filePath) {
if (!file_exists($filePath)) {
throw new Exception("File not found: $filePath");
}
$ch = curl_init();
$cfile = new CURLFile($filePath, mime_content_type($filePath), basename($filePath));
$data = [
'file' => $cfile
];
curl_setopt_array($ch, [
CURLOPT_URL => API_URL,
CURLOPT_POST => true,
CURLOPT_POSTFIELDS => $data,
CURLOPT_RETURNTRANSFER => true,
CURLOPT_HTTPHEADER => [
'Authorization: Bearer ' . API_KEY
]
]);
$response = curl_exec($ch);
$httpCode = curl_getinfo($ch, CURLINFO_HTTP_CODE);
curl_close($ch);
if ($httpCode === 200) {
return json_decode($response, true);
} else {
throw new Exception("API Error: $response");
}
}
// Usage
try {
$result = processOCR('document.pdf');
echo "Extracted Data:\n";
print_r($result);
} catch (Exception $e) {
echo "Error: " . $e->getMessage();
}
?>import requests
import json
API_KEY = 'your_api_key_here'
API_URL = 'https://api.valitract.com/api/v1/extract-generic'
def process_ocr(file_path):
"""
Process OCR on a document using Valitract API
Args:
file_path (str): Path to the document file
Returns:
dict: Extracted data from the document
"""
headers = {
'Authorization': f'Bearer {API_KEY}'
}
with open(file_path, 'rb') as file:
files = {
'file': (file_path, file, 'application/pdf')
}
try:
response = requests.post(API_URL, headers=headers, files=files)
response.raise_for_status()
result = response.json()
return result
except requests.exceptions.RequestException as e:
print(f'Error processing OCR: {e}')
raise
# Usage
if __name__ == '__main__':
try:
data = process_ocr('document.pdf')
print('Extracted Data:')
print(json.dumps(data, indent=2))
except Exception as e:
print(f'Failed to process document: {e}')require 'net/http'
require 'uri'
require 'json'
API_KEY = 'your_api_key_here'
API_URL = 'https://api.valitract.com/api/v1/extract-generic'
def process_ocr(file_path)
uri = URI.parse(API_URL)
File.open(file_path, 'rb') do |file|
request = Net::HTTP::Post.new(uri)
request['Authorization'] = "Bearer #{API_KEY}"
boundary = "-----------RubyMultipartBoundary"
request['Content-Type'] = "multipart/form-data; boundary=#{boundary}"
post_body = []
post_body << "--#{boundary}\r\n"
post_body << "Content-Disposition: form-data; name=\"file\"; filename=\"#{File.basename(file_path)}\"\r\n"
post_body << "Content-Type: application/pdf\r\n\r\n"
post_body << file.read
post_body << "\r\n--#{boundary}--\r\n"
request.body = post_body.join
response = Net::HTTP.start(uri.hostname, uri.port, use_ssl: true) do |http|
http.request(request)
end
if response.code == '200'
JSON.parse(response.body)
else
raise "API Error: #{response.body}"
end
end
end
# Usage
begin
result = process_ocr('document.pdf')
puts "Extracted Data:"
puts JSON.pretty_generate(result)
rescue StandardError => e
puts "Error: #{e.message}"
endusing System;
using System.IO;
using System.Net.Http;
using System.Net.Http.Headers;
using System.Threading.Tasks;
using Newtonsoft.Json;
namespace ValitractOCR
{
public class OCRClient
{
private const string API_KEY = "your_api_key_here";
private const string API_URL = "https://api.valitract.com/api/v1/extract-generic";
public static async Task<string> ProcessOCR(string filePath)
{
using (var client = new HttpClient())
{
client.DefaultRequestHeaders.Authorization =
new AuthenticationHeaderValue("Bearer", API_KEY);
using (var form = new MultipartFormDataContent())
{
var fileContent = new ByteArrayContent(
File.ReadAllBytes(filePath)
);
fileContent.Headers.ContentType =
MediaTypeHeaderValue.Parse("application/pdf");
form.Add(fileContent, "file", Path.GetFileName(filePath));
var response = await client.PostAsync(API_URL, form);
response.EnsureSuccessStatusCode();
var result = await response.Content.ReadAsStringAsync();
return result;
}
}
}
public static async Task Main(string[] args)
{
try
{
var result = await ProcessOCR("document.pdf");
Console.WriteLine("Extracted Data:");
var formatted = JsonConvert.DeserializeObject(result);
Console.WriteLine(
JsonConvert.SerializeObject(formatted, Formatting.Indented)
);
}
catch (Exception ex)
{
Console.WriteLine($"Error: {ex.Message}");
}
}
}
}Get your free API Key
Start for free with complimentary credits and dedicated developer support to help you get set up quickly.
Frequently asked question
Find quick solutions to common queries and get the most out of your learning experience
There are various software tools for data extraction including Python libraries, specialized ETL tools, and custom solutions depending on your specific needs and data sources.
Data extraction allows you to consolidate that information into a centralized system in order to unify multiple data sets.
Yes, Excel can be used for basic data extraction tasks, though it has limitations compared to specialized tools.
There are many free tools available including Python libraries, open-source ETL tools, and free tiers of commercial products.
OCR technology can process various document types including scanned images, PDFs, and photos.
Most systems support CSV, Excel, PDF, JSON, XML, and common image formats.
Modern AI-powered OCR can read clear handwriting, though accuracy varies based on quality.
