❓Why❓

Job offer data is often unstructured, making it difficult to standardize.

HrFlow.ai parsing APIs make it easy for you to structure candidate data. Our API returns a structured JSON object named Job.

🛠️ How to implement 🛠️

You can parse job offers from raw text.

🎓

Prerequisites

1. Create an account
2. Activate your account: you need to activate our Text Parsing API
3. API Authentification
4. Create a board

You need to use our Text Parsing API.

1. Create a board and retrieve its key.
2. Use the Text Parsing API and set parameter output_object to job to retrieve a Job object.
3. Store the parsed Job object in the appropriate source using our Job Indexing API.

❗️

Known bug (will be fixed soon)

By default, our Text Parsing API returns Job with key="".
As the Job Indexing API doesn't override key if non-null, you have to manually set key=None (Python) or key=null (Javascript) in the Job object before using the Job Indexing API.

🎨 Customization 🎨

• You can enrich the Jobobject with tags and metadatas to add more information that is not available from the resume file. Tags are designed to be short and searchable, unlike metadata. More information about tags and metadata here. Both tags and metadatas are objects that must have name (non-null) and they may have a value (nullable)
• If each job already has a unique reference in your system (outside HrFlow.ai), you can set reference field on the Job object.