talentkiwi
IntegrationenAPI-Referenz

Get job results (for async jobs)

GET
/v1/parse/{job_id}/results

Retrieve the parsed results from a completed asynchronous job.

Prerequisites:

  • Job must have completed status (check via /status endpoint)
  • Job must belong to your API key

Response Structure: The results contain structured candidate information including:

  • Personal details (name, contact information)
  • Work experience and employment history
  • Education background
  • Skills and competencies
  • Additional parsed fields based on document content

Authorization

API Key Authentication
X-API-KEY<token>
Enter your secret API key to authorise requests.You can obtain your key by contacting us: gian@dionitech.com**Example**: `sk_live_12345abcde...`

In: header

Path Parameters

job_id*Job Id

Response Body

application/json

application/json

application/json

application/json

application/json

curl -X GET "https://example.com/v1/parse/string/results"
{  "data": {    "personal_info": {      "full_name": "Matteo Guscetti",      "email": "matteo.guscetti@yahoo.com",      "nationality": "Schweiz",      "gender": "Männlich",      "civil_status": "",      "car_license": false,      "birth_date": "1996-12-16",      "mobile_phone": "+41797251712",      "home_phone": "",      "street_and_number": "",      "city": "",      "state": "",      "country": "",      "postal_code": "",      "linkedin": "",      "availability": ""    },    "professional_summary": "Erfahrener Data Scientist mit 2+ Jahren fundierter Expertise in der Entwicklung und Implementierung fortschrittlicher ML-Modelle, einschliesslich Reinforcement Learning und CNNs.",    "personal_impression": "Matteo Guscetti zeigte sich als selbstbewusster, ausgesprochen kommunikativer Kandidat mit hoher Teamfähigkeit.",    "experience": [      {        "id": "exp_1",        "company": "Siemens",        "position": "Data Scientist",        "employment_type": "Praktikum",        "start_date": "01.2022",        "end_date": "07.2022",        "city": "Zürich",        "state": "Zürich",        "country": "Schweiz",        "postal_code": "",        "description_1to1": "Entwicklung eines Reinforcement-Learning-Algorithmus zum Ausgleich von Stromnetzen mit hohem Anteil erneuerbarer Energien.",        "reason_for_change": ""      }    ],    "education": [      {        "id": "edu_1",        "institution": "Eidgenössische Technische Hochschule (ETH) Zürich",        "institution_type": "Universität",        "city": "Zürich",        "state": "Zürich",        "country": "Schweiz",        "postal_code": "",        "degree": "Master in Datenwissenschaft",        "degree_level": "Master",        "field_of_study": "Datenwissenschaft",        "start_date": "02.2020",        "end_date": "07.2022",        "concluded_successfully": true,        "is_further_education": true,        "gpa": "5.51/6",        "description_1to1": "Austauschsemester am Imperial College London im Herbst 2020."      }    ],    "skills": {      "fields_of_experitse": [        "Data Science",        "Machine Learning",        "Business Development"      ],      "hard_skills": [        "Reinforcement Learning",        "Quantitative Analyse",        "Startup Bewertung"      ],      "it_skills": [        "Python",        "PyTorch",        "R",        "SQL",        "Git",        "CNN",        "XGBoost"      ],      "soft_skills": [        "Teamführung",        "Kommunikation",        "Problemlösung"      ]    },    "languages": [      {        "language": "Italienisch",        "standard_proficiency": "C2",        "proficiency": "Muttersprache"      },      {        "language": "Englisch",        "standard_proficiency": "B2",        "proficiency": "gut"      }    ],    "hobbies_interests": [      "Reisen",      "Fotografieren",      "Wandern"    ]  },  "status_code": 200,  "execution_time": 3.45}

Create PDF project from ATS applicants POST

Receive an ATS ``create-pdf`` request, resolve/provision the consultant as a TalentKiwi user, create a project with the requested candidates, kick off background ATS imports, and return a ``redirectUrl`` pointing at the new project. Authentication is via the ``X-Shared-Secret`` header — the same SHA-256 hash lookup used for regular API keys. Steps: 1. Resolve the organisation from the API key. 2. Fetch org-level HR4YOU credentials from ``DomainResourceMapping``. 3. Look up the consultant's e-mail via the HR4YOU ``/consultants/{userId}`` endpoint. 4. Resolve or auto-provision the TalentKiwi user. 5. Create a new project (default open project type). 6. Optionally attach a job post (when ``projectId`` is provided). 7. Create one candidate per ``applicantId``, tag with ATS info. 8. Enqueue a background import per candidate. 9. Return the redirect URL.

Get job status (for async jobs) GET

Check the current status of an asynchronous document parsing job. **Job Statuses:** - `pending`: Job is queued and waiting to be processed - `running`: Job is currently being processed - `completed`: Job finished successfully, results are available - `failed`: Job failed due to an error **Polling Recommendations:** - Check status every 5-10 seconds for small files - Check status every 15-20 seconds for larger files - Stop polling once status is `completed` or `failed`