1. Project Overview:

The project aimed to develop a proof of concept (POC) AI-powered CV matching system within a tight timeframe of 4 to 5 days. This system was designed to streamline the process of matching job descriptions (JDs) with CVs, efficiently identifying the best-fit candidates.

2. Objectives:

• AI Algorithm Development: Create an AI algorithm capable of parsing job descriptions and CVs to identify relevant skills, qualifications, and experience.
• CV Summarization: Implement a feature to provide concise overviews of candidate qualifications.
• Matching Algorithm: Develop a matching algorithm to map each CV to the corresponding JD and assign a suitability score.
• Ranking System: Generate a ranked list of best-fit CVs for each JD based on the matching scores.

3. Scope:

• Input Data Handling:
  • Develop functionality to input job descriptions in text format and store them in a database.
  • Implement bulk upload capability for CVs in PDF format and store them for processing.
• AI Algorithm Development:
  • Design and train a natural language processing (NLP) model to analyze job descriptions and extract key information such as required skills, qualifications, and experience.
  • Develop a CV summarization algorithm to generate concise summaries of candidate profiles.
• Matching Algorithm:
  • Build an algorithm to compare the content of each CV with the corresponding JD and assign a matching score based on relevance.
  • Implement a ranking system to prioritize CVs based on their suitability for each JD.
• User Interface (UI):
  • Develop a minimal web interface during POC for inputting JDs, uploading CVs, and viewing matching results.

4. Deliverables:

• Functional AI algorithm capable of parsing JDs, summarizing CVs, and matching them effectively.
• User interface allowing users to input JDs, upload CVs, and view matching results.
• Documentation detailing system architecture, algorithms used, and instructions for system usage and maintenance.

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LIve Link: https://www.sevenbillion.co/poc

5. Assumptions:

• Availability of sufficient training data for NLP model development.
• Access to necessary infrastructure for model training and deployment.
• Collaboration and feedback from stakeholders to refine the system during development.

6. Constraints:

• The time constraint of 4 to 5 days may limit the depth of system features and optimization.

7. Risks:

• Technical challenges in accurately parsing complex job descriptions and CVs.
• Performance issues in processing large volumes of CVs within the project timeframe.
• Stakeholder expectations may not align with the capabilities of the proof of concept.

8. Stakeholders:

• Project team members responsible for system development, testing, and documentation.
• End users including HR personnel and recruiters who will utilize the CV matching system.
• Project sponsor and key stakeholders providing guidance and feedback throughout the development process.

9. Approval:

This scope and proposal document require approval from the project sponsor and relevant stakeholders before proceeding with project execution.

10. Project Timeline:

• Day 1-2: Requirement analysis and system design.
• Day 3: Development of AI algorithms and UI implementation.
• Day 4: Testing and refinement of system functionality.
• Day 5: Documentation preparation and final review.

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