Question 1

How is iinsights different from an ATS?

Accepted Answer

Traditional ATS platforms rank candidates by keyword frequency against job descriptions — consistent results, but systematically blind to qualified candidates who describe equivalent experience using different terminology. iinsights evaluates candidates across multiple independent dimensions of experience, starting with context before capability. Each dimension produces auditable evidence from the candidate's actual CV, and scores hold within ±5 variance across repeated runs.

Question 2

How is iinsights different from using ChatGPT for resume screening?

Accepted Answer

ChatGPT and other general-purpose LLMs can analyse resumes contextually, but they produce different scores every time you run the same evaluation. A candidate rated 70% on one run might come back at 50% or 90% minutes later. iinsights is engineered for scoring consistency — the same candidate and role evaluated repeatedly will produce the same result within ±5 points. That's the difference between an opinion and a measurement. ChatGPT gives you an opinion. iinsights gives you a measurement your team can standardise around and your clients can trust.

Question 3

What does ±5 scoring variance mean?

Accepted Answer

When iinsights scores a candidate against a role, that score is reproducible. Run the same evaluation today and next month, with different team members, and the result will fall within five points of the original. This is an engineering achievement — raw LLM outputs can swing 20–40+ points between identical runs. iinsights's proprietary multi-pass pipeline constrains and validates all AI outputs to eliminate that instability, producing scores that are consistent enough to present to clients, use for team-wide standardisation, and defend in compliance audits.

Question 4

How does iinsights handle candidates who use different terminology?

Accepted Answer

iinsights's matching methodology detects functional equivalence across different vocabulary. A candidate who writes 'risk governance' instead of 'predictive analytics,' or 'athletic lifestyle brands' instead of 'sporting goods,' is evaluated on what they've actually done — not the specific words they used to describe it. This is the talent that keyword-based systems systematically eliminate, and it's why iinsights produces a demonstrably larger pool of qualified candidates.

Question 5

How does iinsights ingest CVs?

Accepted Answer

iinsights ingests CVs via two channels: direct file upload through the iinsights web application, and automatic email ingestion with multi-tenant routing. Uploaded documents are automatically classified, language-detected, and processed through the matching pipeline. The platform supports bilingual processing in English and Traditional Chinese.

Question 6

Is iinsights suitable for recruiting agencies?

Accepted Answer

iinsights is built for recruiting agencies and staffing firms where missed candidates translate directly to lost placement revenue. The platform surfaces qualified candidates that Boolean searches eliminate, and because every score is reproducible — not a one-time AI opinion — agencies can present recommendations to clients with evidence that holds up to scrutiny. Consistent scoring also means every recruiter on a team produces the same quality of shortlist, not just the best performer.

Question 7

Is iinsights suitable for executive search?

Accepted Answer

Yes. iinsights is particularly effective for senior, specialist, and cross-functional roles where keyword matching fails most severely. The context-first methodology evaluates whether a candidate understands the world a role operates in before assessing specific skills — mirroring how expert recruiters evaluate candidates for senior positions. Every evaluation includes transparent, dimension-level reasoning that can be presented directly to clients.

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