Clara AI’s assessment is precise. It evaluates candidates against job requirements systematically and consistently. But precision without nuance creates a specific problem: candidates who are genuinely qualified get filtered out because their experience doesn’t match the criteria literally.

A warehouse manager who spent three years at an Amazon fulfillment centre has more relevant experience than someone with eighteen months at a traditional 3PL. But if the job says “2 years warehouse experience,” the literal match might miss the better candidate.

Global evaluation rules fix this.

What global evaluation rules do

Global evaluation rules are account-level instructions that tell Clara how to interpret candidate responses and CV data, above and beyond what the job description says.

They act as a calibration layer on top of the standard scoring framework.

Rules apply to all jobs created after they’re saved. They don’t change requirements, they change how Clara understands what a requirement means in your context.

Setting up rules

Navigate to Settings → Context settings. Below the Candidate FAQ section, you’ll find the Global Evaluation Rules text box. Enter your rules in plain text, up to 2,000 characters. Click Save. They apply to every new job from that point forward.

Existing jobs are not affected. Rules are locked in at job creation to ensure all candidates for a given role are evaluated against the same criteria.

What you can define

• Experience equivalents. Tell Clara that certain backgrounds count for more than their CV suggests: “6 months in a fast-paced e-commerce fulfilment centre is equivalent to 1 year of traditional warehouse experience.”

• Certification exceptions. Prevent candidates from being disqualified on administrative technicalities: “Forklift licences that expired within the last two years are acceptable, provided the candidate confirms willingness to renew.”

• Availability nuances. Allow flexibility: “Accept candidates available for rotating shifts even if they initially express a preference for fixed hours.”

• CV-context rules. Guide how Clara interprets work history passed in from a candidate’s CV.

Rules apply globally, not per job

Evaluation rules are account-level. The same rules apply across all job types. If you need different interpretation logic for different roles, you can use conditional language within the same text field.

This keeps the system clean without requiring per-job configuration.

How rules interact with other settings

Rules exist alongside Clara’s other customisation layers:

• Global Evaluation Rules guide how Clara interprets experience and CV data at account level

• The FAQ Knowledge Base addresses what Clara tells candidates about your company

• Knockout Questions handle hard pass/fail pre-screening at job level

• Custom Score Weights control the distribution across Requirements, Skills, and Competencies.

Available as an enterprise add-on

CV context and global evaluation rules are available as an enterprise feature for Clara Pro clients.

If you’re running a high-volume operation where nuanced screening decisions matter, this is where Clara’s consistency advantage compounds most visibly.

Talk to the team about Clara Pro and enterprise features