ParseResumeAI - AI-powered resume parser

API How-to

cURL

curl -X POST 'https://parseresumeai.com/api/parse' \
    -H 'Authorization: Bearer YOUR_API_KEY' \
    -d '{ "file": "https://parseresumeai.com/resume-samples/resume.pdf" }'

cURL with file

curl -X POST 'https://parseresumeai.com/api/parse' \
    -H 'Authorization: Bearer YOUR_API_KEY' \
    -F 'file=@resume.pdf'

JavaScript

const formData = new FormData();
formData.append('file', fileInput.files[0]);

fetch('https://parseresumeai.com/api/parse', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY'
  },
  body: formData
})
.then(response => response.json())
.then(data => console.log(data));

PHP

$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, 'https://parseresumeai.com/api/parse');
curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1);
curl_setopt($ch, CURLOPT_POST, 1);
curl_setopt($ch, CURLOPT_POSTFIELDS, [
    'file' => new CURLFile('/path/to/resume.pdf')
]);
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    'Authorization: Bearer YOUR_API_KEY'
]);

$result = curl_exec($ch);
curl_close($ch);

Python

import requests

url = 'https://parseresumeai.com/api/parse'
headers = {'Authorization': 'Bearer YOUR_API_KEY'}
files = {'file': open('resume.pdf', 'rb')}

response = requests.post(url, headers=headers, files=files)
print(response.json())

Ruby

require 'net/http'
require 'uri'

uri = URI.parse('https://parseresumeai.com/api/parse')
request = Net::HTTP::Post.new(uri)
request['Authorization'] = 'Bearer YOUR_API_KEY'
request.set_form([['file', File.open('resume.pdf')]], 'multipart/form-data')

response = Net::HTTP.start(uri.hostname, uri.port, use_ssl: true) do |http|
  http.request(request)
end

.NET

using (var client = new HttpClient())
{
    client.DefaultRequestHeaders.Add("Authorization", "Bearer YOUR_API_KEY");
    
    var content = new MultipartFormDataContent();
    content.Add(new StreamContent(File.OpenRead("resume.pdf")), "file", "resume.pdf");
    
    var response = await client.PostAsync("https://parseresumeai.com/api/parse", content);
    var result = await response.Content.ReadAsStringAsync();
}

Go

file, _ := os.Open("resume.pdf")
defer file.Close()

body := &bytes.Buffer{}
writer := multipart.NewWriter(body)
part, _ := writer.CreateFormFile("file", "resume.pdf")
io.Copy(part, file)
writer.Close()

req, _ := http.NewRequest("POST", "https://parseresumeai.com/api/parse", body)
req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
req.Header.Set("Content-Type", writer.FormDataContentType())

client := &http.Client{}
resp, _ := client.Do(req)

Sample Output

{
  "parsed": {
    "name": "David Patel",
    "title": "Lead Data Scientist",
    "brief": "PhD-level Data Scientist with 6 years of experience applying machine learning and statistical analysis to solve complex business problems. Specialized in NLP, computer vision, and predictive modeling.",
    "contact": {
      "location_city": "Seattle",
      "location_state": "Washington",
      "location_country": "USA",
      "email": "david.patel@email.com",
      "phone": "+1 (206) 555-9012",
      "linkedin": "https://www.linkedin.com/in/davidpatel",
      "github": "https://github.com/dpatel",
      "twitter": null,
      "website": "https://davidpatel.dev"
    },
    "employment_history": [
      {
        "title": "Lead Data Scientist",
        "company": "CloudAI Technologies",
        "company_website": null,
        "location": "Seattle, WA",
        "start_date": "2021-07-01",
        "end_date": null,
            "responsibilities": [
          "Lead data science team of 5 in developing ML models for customer churn prediction",
          "Built recommendation engine processing 10M+ user interactions daily",
          "Deployed NLP models for sentiment analysis with 94% accuracy",
          "Reduced model training time by 40% through distributed computing optimization",
          "Established MLOps best practices and model monitoring infrastructure"
        ]
      },
      {
        "title": "Data Scientist",
        "company": "DataInsights Corp",
        "company_website": null,
        "location": "San Francisco, CA",
        "start_date": "2018-08-01",
        "end_date": "2021-06-30",
            "responsibilities": [
          "Developed predictive models improving sales forecasting accuracy by 30%",
          "Created automated data pipelines processing 1TB+ daily data",
          "Implemented A/B testing framework for product experiments"
        ]
      }
    ],
    "education": [
      {
        "degree": "Doctor of Philosophy (PhD) in Computer Science",
        "institution_name": "Stanford University",
        "institution_country": "USA",
        "start_date": null,
        "end_date": "2018"
      },
      {
        "degree": "Master of Science in Data Science",
        "institution_name": "University of California, Berkeley",
        "institution_country": "USA",
        "start_date": null,
        "end_date": "2016"
      }
    ],
    "certifications": [
      "AWS Certified Machine Learning - Specialty",
      "TensorFlow Developer Certificate",
      "Kaggle Expert (3x Competition Winner)"
    ],
    "skills": [
      "Python", "R", "SQL",
      "TensorFlow", "PyTorch", "Scikit-learn",
      "Deep Learning", "NLP", "Computer Vision",
      "AWS", "Docker", "Spark"
    ],
    "courses": [],
    "languages": ["English", "Hindi", "Gujarati"],
    "awards": [
      "Stanford AI Lab Outstanding Research Award",
      "Kaggle Expert (3x Competition Winner)"
    ],
    "derived": {
      "years_of_experience": 6,
      "approximate_age": 32
    }
  },
  "meta": {
    "filename": "data-scientist-resume.txt",
    "file_type": "txt",
    "file_size": 4512,
    "file_hash": "7b8e3f92a1c4d56f89e0b2a3c1d4e5f6",
    "status": "success",
    "processing_time": 1.23,
    "error_message": null,
    "cost": 0.07,
    "balance_before": 5.00,
    "balance_after": 4.93,
    "source": "api"
  }
}

Powerful Resume Parsing Features

Multi-Format Support

Seamlessly parse PDF, DOC, DOCX, TXT, and image files (PNG, JPG, JPEG).

Dependable

99.9% uptime, ensuring the API is always available when you need it.

Lightning Fast

Parse resumes in seconds with our high-performance API.

Structured Data Extraction

Extract names, contact info, experience, education, skills, certifications, and more.

No Training Required

Works out of the box with zero setup. Just upload a resume and get structured data back instantly.

Secure & Private

Your data is yours. We don't store resumesor any extracted data.

Extract structured data from
resumes with just one API call

API How-to

cURL

cURL with file

JavaScript

PHP

Python

Ruby

.NET

Go

Sample Output

Powerful Resume Parsing Features

Multi-Format Support

Dependable

Lightning Fast

Structured Data Extraction

No Training Required

Secure & Private

Pricing

Frequently Asked Questions

Ready to transform your recruitment process?

Extract structured data fromresumes with just one API call

API How-to

cURL

cURL with file

JavaScript

PHP

Python

Ruby

.NET

Go

Sample Output

Powerful Resume Parsing Features

Multi-Format Support

Dependable

Lightning Fast

Structured Data Extraction

No Training Required

Secure & Private

Pricing

Frequently Asked Questions

Ready to transform your recruitment process?

Extract structured data from
resumes with just one API call