First, fetch active job postings: Start by pulling all active job postings from the connected ATS provider using x-account-id in the request header. This will give you details like title, content, locations, compensation, and more.

• API Endpoint: GET /ats/job_postings

Next, pull recent applications: Fetch all candidate applications updated within the last month by setting the updated_after query parameter (e.g., 2024-08-01T00:00:00.000Z) to ensure your SaaS dashboard has the latest applications.

• API Endpoint: GET /ats/applications

Retrieve associated candidate data: For each application, retrieve the associated candidate information, including name, email, social_links, phone, and Resume. This data will be displayed alongside the application on your SaaS dashboard for easy review and analysis.

• API Endpoint: GET /ats/candidates/{id}

First, set up webhooks for application updates: Configure webhooks to automatically sync updates for existing applications, such as interview_stage, rejected_reasons, and application_status, or capture new ones as soon as they are created. Hence, the dashboard always has the most current application data.

• Webhook Events: ats_applications.updated or ats_applications.created

Next, sync candidate updates: Similarly, set up webhooks to sync candidate information whenever there are updates or new candidates are added. This keeps your system up to date with the latest candidate details.

• Webhook Events: ats_candidates.updated or ats_candidates.created

Trigger AI screening system: Set up a webhook to trigger the intelligence system, which automatically screens and scores applications as they are updated or newly added. This ensures real-time evaluation and decision-making.

Store fetched data: Now, store fetched data, such as application_id, candidate_id, job_id, interview_stage, application_status, candidate details, and resumes in your database to facilitate real-time screening and analysis.

Centralize candidate information: Keeping all data in one place ensures quick access to applications and candidate details for processing and HR decisions.

After applications and candidate details are fetched from the ATS via the recruitment SaaS, they will be screened by an intelligent AI system. The AI will carry out the following operations in the recruitment process:

Remove bias and fetch profiles: AI will remove any bias related to gender, race, or culture when evaluating candidates. It will also fetch LinkedIn profiles along with the applications(from the ATS) for a complete analysis.

Score applications based on criteria: AI scores each application using criteria set by HR, using NLP to analyze applications against job descriptions.

Automate actions and emails: Based on the AI score, the system will automatically or manually move candidates to stages like Shortlisted, Paused, or Rejected, etc, and can send personalized rejection or shortlisted emails to candidates at scale.

• API Endpoint: PATCH ats/applications/{id}

Store scores and analysis: The AI-generated score, application status, and detailed analysis for each candidate will be stored in the database, ensuring easy access for future reference and reporting.