AI APIs for HR Tech Platforms
One API suite for the whole recruitment pipeline: parse resumes into clean JSON, score candidates against job offers, expand skills taxonomies and generate job descriptions — without training a single model.
Parse a Resume Right Now
Pick a sample resume and watch the parser return the structured JSON your ATS would consume.
Try it live — no signup needed
Live demoPick a sample document and watch this API process it in real time.
That was a live API response. Get your own API key and 100,000 free trial words — no credit card required.
Double opt-in, unsubscribe anytime.
Try it live — no signup needed
Live demoPick a sample resume, paste a job description and watch the AI score the match.
That was a live API response. Get your own API key and 100,000 free trial words — no credit card required.
Double opt-in, unsubscribe anytime.
Try it live — no signup needed
Live demoPaste a short text and watch this API process it in real time.
That was a live API response. Get your own API key and 100,000 free trial words — no credit card required.
Double opt-in, unsubscribe anytime.
Try it live — no signup needed
Live demoPaste a short text and watch this API process it in real time.
That was a live API response. Get your own API key and 100,000 free trial words — no credit card required.
Double opt-in, unsubscribe anytime.
Try it live — no signup needed
Live demoPaste a short text and watch this API process it in real time.
That was a live API response. Get your own API key and 100,000 free trial words — no credit card required.
Double opt-in, unsubscribe anytime.
One Async Workflow for Every Endpoint
Integrate the pattern once and every HR endpoint works the same way.
1. Submit
POST a resume file or text payload. The API immediately returns a job ID and a status_url — no blocking requests in your web workers.
2. Poll
Poll the status_url or let an SDK handle it. Jobs run asynchronously in a processing queue, typically finishing in seconds.
3. Consume JSON
Get a documented, stable JSON schema per endpoint — candidate profiles, match scores or skill lists ready for your database.
Call it from any stack
Submit a job, poll the status URL, get structured JSON. SDKs available for PHP, Laravel, Python, Node.js, .NET and Flutter.
curl -X POST "https://sharpapi.com/api/v1/hr/parse_resume" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"file": "resume.pdf (multipart/form-data — PDF, DOC, DOCX or TXT)", "language": "English"}'$response = Http::withToken('YOUR_API_KEY')
->post('https://sharpapi.com/api/v1/hr/parse_resume', {"file": "resume.pdf (multipart/form-data — PDF, DOC, DOCX or TXT)", "language": "English"});
$statusUrl = $response->json('status_url'); // poll until status = successimport requests
response = requests.post(
"https://sharpapi.com/api/v1/hr/parse_resume",
headers={"Authorization": "Bearer YOUR_API_KEY"},
json={"file": "resume.pdf (multipart/form-data — PDF, DOC, DOCX or TXT)", "language": "English"},
)
status_url = response.json()["status_url"] # poll until status == "success"{
"data": {
"type": "api_job_result",
"id": "50fa96a0-3e34-4323-be84-6ed602b00925",
"attributes": {
"status": "success",
"type": "hr_parse_resume",
"result": {
"candidate_name": "Jack Doe",
"candidate_email": "johndoe@gmail.com",
"candidate_phone": "+1 888 888 8888",
"candidate_address": "",
"candidate_language": "English",
"candidate_spoken_languages": [
"English"
],
"candidate_honors_and_awards": [
"Third best project in Machine Learning Practical by IBM"
],
"candidate_courses_and_certifications": [],
"candidate_linkedin": "",
"candidate_github": "",
"candidate_twitter": "",
"candidate_website": "",
"candidate_date_of_birth": null,
"candidate_nationality": "",
"candidate_summary_objective": "",
"work_authorization": "",
"years_of_experience": 2,
"approximate_age": null,
"brief_summary": "John Doe is a skilled software engineer with experience in Android development and a strong academic background in artificial intelligence and computer science.",
"drivers_licenses": [],
"interests_hobbies": [],
"projects": [
{
"project_name": "Image Classification",
"description": "Classified images of handwritten digits and letters from the MNIST and EMNIST datasets using deep neural networks. Implemented models with different activation functions, weight initialization strategies, and learning rules.",
"url": ""
},
{
"project_name": "Speaker Independent Digit Recognition",
"description": "Recorded voiced English digits and parameterized the collected waveform files as MFCCs. Constructed a speaker-dependent, and -independent speech recognizer using the Hidden Markov Model Toolkit (HTK).",
"url": ""
}
],
"volunteer_experience": [],
"publications": [],
"references": [],
"positions": [
{
"position_name": "Software Engineer Internship",
"company_name": "Google Inc.",
"country": "Japan",
"start_date": "2017-05-01",
"end_date": "2017-07-31",
"skills": [
"Android",
"Google Maps",
"Interactive screenshot code generator"
],
"job_details": "Designed and implemented an interactive screenshot code generator for Android Google Maps."
},
{
"position_name": "Visiting Student Research Internship",
"company_name": "Brown University",
"country": "USA",
"start_date": "2017-01-01",
"end_date": "2017-04-30",
"skills": [
"Statistical analysis",
"User interactions",
"Crowdsourcing system"
],
"job_details": "Performed statistical analysis on user interactions for the crowdsourcing system 'Drafty' HCOMP 2017. Advisor: Jeff Huang."
},
{
"position_name": "Software Engineer Internship",
"company_name": "Google Inc.",
"country": "Japan",
"start_date": "2016-09-01",
"end_date": "2016-12-31",
"skills": [
"Android",
"Chrome",
"WebView",
"Language locales",
"Han character unification"
],
"job_details": "Created support for multiple language locales in Android Chrome and WebView. Fixed Han character unification in Android Nougat. Made locales consistent across all Chrome supported Android Versions."
},
{
"position_name": "Summer Trainee Engineering Program Internship",
"company_name": "Google Inc.",
"country": "Japan",
"start_date": "2015-05-01",
"end_date": "2015-09-30",
"skills": [
"Bug assignment system",
"Google's internal bug organizer"
],
"job_details": "Improved the bug assignment system in Google’s internal bug organizer."
}
],
"education_qualifications": [
{
"school_name": "The University of Edinburgh, School of Informatics",
"school_type": "University or equivalent",
"degree_type": "Master's Degree or equivalent",
"faculty_department": "",
"specialization_subjects": "Artificial Intelligence",
"country": "United Kingdom",
"start_date": "2017-09-01",
"end_date": "2018-11-30",
"learning_mode": "In-person learning",
"education_details": "Master of Science with Distinction in Artificial Intelligence."
},
{
"school_name": "University of Toronto, Faculty of Arts and Sciences",
"school_type": "University or equivalent",
"degree_type": "Bachelor's Degree or equivalent",
"faculty_department": "",
"specialization_subjects": "Computer Science and Mathematics",
"country": "Canada",
"start_date": "2012-08-01",
"end_date": "2016-06-30",
"learning_mode": "In-person learning",
"education_details": "Honors Bachelor of Science with Distinction in Computer Science and Mathematics."
},
{
"school_name": "Waseda University, School of Fundamental Science and Engineering",
"school_type": "University or equivalent",
"degree_type": "N/A",
"faculty_department": "",
"specialization_subjects": "",
"country": "Japan",
"start_date": "2014-08-01",
"end_date": "2015-07-31",
"learning_mode": "In-person learning",
"education_details": "One year Exchange Program (University of Toronto)."
}
]
}
}
}
}The Complete HR Tech Endpoint Suite
AI endpoints for the candidate pipeline plus utility databases for skills and job title taxonomies.
Análisis de CV
Analiza un archivo de currículum (DOC, DOCX, TXT, RTF, PDF, JPG, JPEG, JPE, PNG, TIFF, TIF) y devuelve puntos de datos detallados.
Puntuación de coincidencia de trabajo de currículum/CV
Evaluación inteligente de IA para la compatibilidad entre CV y trabajo
Generador de Descripción de Trabajo
Crea una descripción detallada del trabajo adaptada a una amplia gama de parámetros.
Generador de habilidades relacionadas
Genera una lista de habilidades relacionadas con sus correspondientes puntuaciones de relevancia.
Generador de posiciones laborales relacionadas
Genera una lista de puestos de trabajo relacionados junto con sus puntuaciones de relevancia.
API de Base de Datos de Habilidades
Utility API: query a curated database of professional skills for autocomplete, normalization and taxonomy features.
Endpoint details →API de Puestos de Trabajo
Utility API: look up standardized job titles to power search filters, role suggestions and clean position data.
Endpoint details →What HR Platforms Build with SharpAPI
ATS Resume Intake
Turn every uploaded resume into a searchable candidate profile the moment it lands — no manual data entry.
Automated Candidate Ranking
Score each applicant against the job description and surface the strongest matches first for recruiters.
Job Board Posting Tools
Give employers a one-click job description generator with requirements and benefits drafted by AI.
Skills-Based Search
Expand queries with related skills so a search for "React" also finds candidates listing "Next.js".
Career Path Suggestions
Recommend adjacent roles to candidates using the Related Job Positions endpoint and weighted results.
Profile Autocomplete
Back your onboarding forms with the Skills and Job Positions databases for clean, normalized inputs.
Why HR Tech Vendors Choose SharpAPI
Layout-Agnostic Parsing
One JSON schema for every resume template — two-column designs, tables and scanned exports included.
Explainable Match Scores
Match results ship with reasoning, so recruiters see why a candidate ranked high — not just a number.
Taxonomy Databases Included
Skills and Job Positions utility APIs replace expensive enterprise taxonomy licenses.
Multilingual Pipeline
Parse resumes and generate job content in the language your market needs — 80+ supported.
Async & Batch-Friendly
The job/poll workflow processes thousands of resumes overnight without tying up your servers.
SOC 2 Type II Certified
Candidate documents are handled under an audited security program — a hard requirement for HR data.
Predictable pricing from $50/month
14-day free trial with 100,000 words included. No credit card required. 30-day money-back guarantee on your first payment.
HR Tech APIs — Frequently Asked Questions
-
The HR suite covers the full candidate pipeline: Resume/CV Parsing to structured JSON, Resume-to-Job Match Scoring, Related Skills and Related Job Positions generators, and an AI Job Description Generator. Two utility databases — Skills Database API and Job Positions API — complement them with taxonomy lookups.
-
The Resume/CV Parsing API accepts PDF, DOC, DOCX and TXT files sent as multipart/form-data. It returns one consistent JSON structure with personal details, work history, education, skills, languages and certifications — regardless of the resume layout.
-
You submit a candidate resume file together with a job description text. The API returns a structured match score with an explanation, so your ATS can rank applicants automatically instead of relying on keyword filters.
-
Yes — that is the intended design. Parse the resume first, score it against your job description, expand candidate skills with the Related Skills endpoint for better search, and generate the job posting itself with the Job Description Generator. All endpoints share the same auth, job workflow and JSON conventions.
-
Processing is API-based and asynchronous; submitted documents are used only to produce your job result. SharpAPI is SOC 2 Type II certified — see the trust portal for the current security posture and policies.
-
All endpoints share one subscription starting at $50/month, metered in processed words. New accounts get a 14-day free trial with 100,000 words — enough to benchmark parsing quality on your own resumes.
Add AI to Your HR Product This Week
Start the 14-day free trial and benchmark resume parsing on your own documents — 100,000 words included.
No se requiere tarjeta de crédito