Applicant screening with human review
How do I screen inbound job applicants automatically?
Automatically screen inbound job applicants by turning each application into structured, job-related evidence, comparing it against the same written criteria, and producing a ranked shortlist with reasons.
Use the result as decision support, not a final hiring decision, and require a person to review the evidence before anyone is contacted or rejected.
Answered by Floom · Updated
The goal is consistent preparation, not automated judgment about a person's worth. A useful worker extracts the same role-relevant facts from every application and shows how each recommendation relates to the rubric.
Write the rubric before connecting the trigger. Separate required qualifications from preferences, define what counts as evidence, and exclude protected characteristics or proxies that are not relevant to the work.
How it works
Create a reviewable applicant shortlist
- 01
Capture each application
Trigger the worker from a new application, an email, or a webhook from the hiring flow. Keep the original application available for the reviewer.
- 02
Extract the same evidence
Turn the CV and answers into a consistent profile covering the written, job-related criteria without filling gaps with guesses.
- 03
Compare with the rubric
Score or group candidates against the same requirements and include a short reason with the evidence behind every recommendation.
- 04
Send a shortlist for review
Give the hiring owner the profiles, scores, reasons, and uncertainty. A person decides who advances and which message, if any, is sent.
Floom example
A concrete Floom example: Candidate Screener
Floom includes recruiting worker patterns that rank a candidate shortlist from a mandate with per-candidate reasoning and turn raw CVs into structured candidate profiles. A Candidate Screener can combine those steps for inbound applications.
For a new application, the worker can read the submitted CV and role answers, extract evidence for the agreed rubric, and prepare a shortlist entry with a reason. It can run from the application trigger without making the final hiring decision.
The hiring owner reviews the original evidence and the worker's reasoning. Outreach remains optional and can be held for approval, so screening assistance does not silently become an automated acceptance or rejection system.
Frequently asked questions
Short answers to the next questions.
- Can AI make the final hiring decision?
- Use AI for structured preparation and decision support, not the final decision. A person needs to review the source evidence, the rubric, and the worker's reasoning before advancing or rejecting an applicant.
- What criteria can an applicant screener use?
- Use written, job-related criteria such as required experience, demonstrated skills, location or work authorization when lawfully relevant, and evidence from the application. Do not use protected characteristics or unsupported inferences.
- Can the worker explain why it ranked someone?
- Yes. Make per-candidate reasoning a required output and ask it to point back to the application evidence for each criterion. The reviewer can then verify or disagree with the result.
- Can applicant outreach require approval?
- Yes. Keep any email or external message as a separate step and require approval in Slack or by email before it is sent. Screening output alone does not need permission to contact a candidate.
A worker for the repeated work
Describe the job. Keep the approval.
Floom runs AI workers in the background and asks before outward-facing work moves forward.