Clara AI: The core engine behind smarter hiring decisions
4 min read
Most hiring tools rely on keyword filters and binary pass/fail rules. That approach removes nuance. A candidate with four years instead of five is rejected. Transferable skills are overlooked.
Clara AI works differently.
It reads the job description, generates a structured interview, conducts the call, and scores each answer against a defined rubric. Candidates are classified from Poor Fit to Outstanding.
Recruiters see a ranked shortlist with clear, structured justifications — not a pile of CVs.
How Clara AI turns a job description into a structured evaluation
When a hiring manager creates a role, Clara AI parses the job description and extracts three categories of criteria:
Requirements such as education, years of experience, and certifications
Skills including tools, technical knowledge, and domain expertise
Competencies like communication, teamwork, and problem-solving
Each criterion is classified as mandatory or optional. This distinction matters later, because it determines how much weight each one carries in the final score.
From there, Clara AI generates a complete interview script. Requirements get 1 to 3 questions each, depending on complexity. Skills and competencies each get one targeted question. Every question comes with a pre-generated rubric: six confidence levels from Excellent to Inadequate, each with a custom description written for that specific criterion.
This rubric is the gold standard. Clara AI does not guess. She compares every candidate answer against these reference descriptions and assigns a raw score from 1 to 100.
Why weighted scoring catches what keyword filters miss
Raw scores alone are not enough. A candidate who aces an optional skill but falls short on a mandatory requirement should not outscore someone who meets every core criterion.
Clara AI applies a two-layer weighting system to solve this:
Importance layer - Mandatory criteria account for 80% of the score, optional criteria for 20%
Category layer - Requirements carry 45% weight, Skills carry 45%, and Competencies carry 10%
Consider Sarah, a candidate for a warehouse operative role at Acme Logistics. She scores 90 on the mandatory forklift certification (Requirements), 70 on inventory management software (Skills), but only 50 on a nice-to-have first aid certification (Optional). The weighting system ensures her strong performance on the mandatory requirement drives the final score, rather than being dragged down by an optional gap.
This is the difference between a filter and an evaluation. Filters discard. Clara AI's engine evaluates, weighs, and ranks.
From score to shortlist: how classification gives recruiters a clear starting point
Here is the revised version with the star system removed, keeping only the product labels:
The weighted calculation produces a final classification, mapped to a clear, human-readable outcome:
Outstanding: Exceptional performance across core competencies
Great: Strong match on key requirements
Good: Solid fit, meets expectations
Average: Below expectations in important areas
Low: Significant gaps in core competencies
Poor: Does not meet mandatory requirements
Recruiters see each candidate’s classification, their breakdown by competency, and a structured written summary explaining how Clara reached the conclusion.
Every result is explainable. Each outcome is tied to specific answers, measured against a defined rubric.
For a team hiring 50 warehouse operatives, this means opening Clara’s dashboard to find candidates already interviewed, classified, and ranked.
Instead of spending days screening CVs and running first-round calls, they review structured reports and decide who to move forward.
The recruiter makes the final decision. Clara handles the volume.
What this means for your hiring team
The core engine saves recruiters an estimated 15 to 20 hours per role on screening and early-stage evaluation. For teams hiring across multiple roles simultaneously, that is the difference between hiring another coordinator and getting more from the people you already have.
Time that used to go toward reading CVs, scheduling calls, and writing up notes now goes toward meeting shortlisted candidates, preparing hiring managers for interviews, and making better decisions faster.
Clara AI's core engine is available to all users.
