Current parsers do not reliably detect all candidate experiences or wrongly introduce non-existing ones. This means that your current features do not work effectively. Also, you might not even have launched features that can increase your software's potential in automating recruitment processes or improving the candidate experience. Our parser enables:

• More job applications: with precise pre-population of application forms job candidates need to enter less data manually leading to more completed applications
• Faster hiring: Detect great candidates automatically and invite them to an interview minutes after their application
• Find suitable candidates from your CV database of internal and external candidates
• Re-skilling / up-skilling: Understand and map capabilities of current employees
• Get analytics on your candidates and remove bias

CVandMe has built its parser from scratch using

• GPT-3 language models finetuned on proprietary data
• Deep image segmentation and classification models

GPT-3 is one of the best deep learning models to understand text. It was developed by OpenAI and has 175 billion parameters. CVandMe has been part of the few beta testers since its launch in 2020. We also employ deep learning models to detect visual features of single words in a CV and to segment a CV into logical areas.

CVandMe is superior for parsing

• CVs in image format (jpg, png) or in pdf-format with text embedded as images
• CVs with 2 or 3 columns
• Distinguishing major skills (developed frontend in JS) from minor ones (reported on JavaScript project)