Saves Time: Automatically generates screening criteria from the job description or landing page, eliminating manual setup.

Reduces Bias: Applies objective criteria to evaluate all candidates fairly.

Improves Quality: Scores and sorts candidates to highlight those best suited for the role.

Boosts Efficiency: Automatically move candidates individually or in bulk to specific stages based on score thresholds.

Supports Data-Driven Hiring: Provides clear, quantifiable scores for informed decision-making.

AI powered CV Screening is an optional add-on that needs to be activated by your Customer Success Manager. For a quote and demo of the feature please contact your dedicated CSM or email: [email protected]

Once the feature has been activated, make sure you have a Job Description saved in the edit project view OR have a job ad landing page with the roles responsibilities and requirements listed and linked to the project. The more specific the better, but try and avoid listing requirements which can be too subjective or deemed as discriminatory.

Automatically generate screening criteria based on the contents of the job description and/or the associated job ad landing page (or add criteria manually)

Teamdash AI will now create a table with the candidates and criteria listed:

Criteria can be added, edited, deleted or marked as required. Marking required will put a heavier weighting on the score for that criteria.

Running the screener will now look at each criteria and using AI, assess each candidate based on the contents of their CV.

If the AI detects any potentially unsuitable criteria you will receive a warning, with the ability to include the criteria anyway or remove it before completing the screening.

Once the screener has run (in a matter of seconds), the highest scoring candidates appear at the top of the list, with further insights available by hovering over each symbol.

Candidates can be moved to another stage one by one using the drop down to the right of their score.

Or use the sorting feature to set a score threshold, then move multiple candidates with a higher or lower score than the threshold to a specified stage.

Make sure you have well written job descriptions with the necessary skills, experience and qualifications listed.

Try to avoid any criteria that could exclude great candidates (years of experience for example).

Try not to list anything that could be too subjective.

AI isn't perfect, humans still need to have the final say and should always review before making final decisions.