AI CV Library
A multinational IT services company engaged Beyondsoft to help its recruitment team turn a large volume of scattered CVs into a structured, searchable talent resource.
The solution combines document processing, data structuring and AI-assisted candidate matching to help recruiters find relevant talent more efficiently while retaining human control over hiring decisions.
The challenge
The client’s recruitment team managed CVs and candidate information across multiple files and formats.
This made it difficult to search consistently across past applicants, compare candidate experience and skills, or identify relevant profiles for new roles. Recruiters needed a way to transform unstructured CVs into a more useful and reusable talent pool.
Our solution
Beyondsoft developed an AI-powered CV library that converts uploaded CVs into structured candidate profiles.
The solution retains both the original document and the parsed output, while normalising candidate information into a consistent Markdown format.
A large language model assists with interpreting and classifying relevant details, including:
- Work history and project experience
- Skills and areas of expertise
- Industry knowledge
- Languages and certifications
- Relevant candidate tags
Smarter search and matching
Recruiters can search the CV library by keyword, skill, experience and tag.
When a job description is created, the system retrieves and matches suitable candidate profiles. It also shows the basis for each match, the requirements already covered and the areas that may need further confirmation.
Human-led recruitment decisions
The solution is designed to support recruiters, not replace their judgement.
Recruiters remain responsible for reviewing candidate recommendations and making decisions. Sensitive contact details are permission-controlled and are not passed to the AI model.
What it enables
The AI CV Library helps recruitment teams create a more organised and accessible talent resource.
It supports faster candidate discovery, more consistent profile comparison and better reuse of existing candidate information across recruitment activities.