hr-oxy-poc / README.md
AI-Powered Automated CV Screening for OXY HR
Last updated: 4/16/2026GitHub
AI-Powered Automated CV Screening for OXY HR
Full Solution Scope (Post-POC Vision)
The full solution will integrate directly with Workday, OXY's HR system, and include:
-
Automated CV Ingestion
- Applications are automatically received in Workday.
- Siraaj Agent retrieves and queues new applications.
-
AI-Powered Screening
- Siraaj Agent evaluates each CV using role-specific criteria, rubrics, and requirements provided by OXY HR.
- Generates a scoring summary for each candidate.
-
Recommendation & Feedback Loop
- Posts a report and recommendation back to Workday.
- Optionally auto-approves or auto-rejects candidates based on HR-configured thresholds.
-
Continuous Improvement
- HR can provide feedback on AI evaluations to refine accuracy over time.
POC Scope
The POC will be a simplified demonstration of the above process, focused on proving feasibility and value.
In-Scope Activities:
- Test CVs will be uploaded through a simple web interface.
- A sample job description and screening criteria will be provided by OXY HR.
- Siraaj Agent will:
- Analyze each test CV against the job description and criteria.
- Generate a summary report and screening recommendation.
- Provide an output report viewable via the web interface.
Out-of-Scope (For POC):
- Direct integration with Workday.
- Automatic approval/rejection in production systems.
- Screening of live/real applicant data (only test data will be used).
Problem Statement
- Manual CV screening is time-consuming and repetitive.
- It creates bottlenecks in the recruitment process.
- There is inconsistency in evaluations due to human subjectivity.
- Scaling up recruitment during peak hiring periods is challenging.
Supporting documents
N/A
Getting started
Pre-requisites
Project setup
Clone the repository
git clone git@github.com:rihal-om/hr-oxy-poc.git
cd hr-oxy-poc
Running the app locally
-
Create and fill
.env -
Run docker-compose to start the application
docker-compose up
- Once the application is running, open your browser and navigate to:
# FastAPI Endpoints
http://localhost:8000/docs
# Streamlit Frontend
http://localhost:8501
Tech Stack
| Category | Tool | Description |
|---|---|---|
| Frontend | Streamlit UI | UI library/framework |
| Backend | FastAPI + LangGraph | Server-side language/framework |
| Containerization | {{DOCKER}} | Container platform |
Project Team
| Name | Role | GitHub |
|---|---|---|
| Bushra Al Jahwari | Machine Learning Engineer | @bushrxh |
Feel free to reach out to any of us for questions, feedback, or collaboration opportunities. We are always open to discussing new ideas and improvements for the project.
Happy coding!