How intothe.zone uses AI

What is AI-scored

Every match you see carries a Zone Score (0–100). It is a weighted blend of five dimensions we compute about the fit between you and a specific role: skill fit, mission fit, work-style (psychometric) fit, energy fit, and career-trajectory fit — plus a small adjustment for how credible the company's role posting looks. Skill fit combines keyword matching with semantic similarity between your profile and the role description, computed using machine-learning embeddings.

The score arithmetic itself is deterministic software, not a chatbot. Large language models are used in two places around it: extracting a structured profile from your CV, and writing the plain-English explanations of a score you see on each match. Match explanations, application drafts, CV suggestions, interview practice, and the career coach chat are AI-generated text — always review them before you rely on them.

If your feedback over time shows you weigh some dimensions differently, your personal scoring weights adapt — only from your own feedback, never from other users' data. Each score also shows an AI confidence figure: the less we know about you (no psychometrics, few calibrations), the lower it is.

Work-style and energy fit

Two of the five dimensions — work-style fit and energy fit, 20% of a Zone Score each — come from your Work DNA questionnaire answers and your ratings of past roles. Work-style results are special category data under Article 9 GDPR, so we keep and use them only with your explicit consent.

Without them, those two dimensions score a neutral 50 and the AI confidence figure is lower. You can withdraw consent at any time under Profile → Work DNA (“Withdraw consent”): your results are deleted, the work-style scores derived from them are removed from your matches, and your matches are rescored. Ratings of past roles can be edited or deleted on the Zone Calibration page.

What data is used

• The CV you upload, and any career context or corrections you add
• A LinkedIn data export or GitHub connection, if you choose to provide them
• Your psychometric questionnaire answers and zone calibrations (ratings of past roles)
• Job postings and company information gathered from public sources
• Your in-product feedback (saved, applied, dismissed matches; match-quality ratings)

We do not collect protected characteristics (such as age, gender, ethnicity, disability, or religion) and do not use them in scoring. Parts of this data are processed by our AI vendors (OpenAI and Anthropic) to extract your profile, compute embeddings, and generate explanations.

Scores are advisory — you decide

A Zone Score is a recommendation to you, and nothing more. It does not gate anything: you can view and apply to any role regardless of its score. No employer or recruiter ever sees your scores, your matches or your Work DNA — they exist only inside your account. If you choose to work with a recruitment agency, it sees only the profile details you select on your share card, and never a score or any other evaluation made by our AI (see our privacy policy). intothe.zone makes no automated decision about you that has legal or similarly significant effects (the kind restricted by Article 22 GDPR); the only decision downstream of a score is the one you make yourself. If we ever build features that share any evaluation of you with an employer, they will be opt-in and this page will change first.

How to correct or recalibrate

• Re-upload your CV or edit your profile at any time — scores recompute
• If the AI infers a skill gap that's wrong, flag it on your profile; your correction overrides the inference permanently
• Redo your zone calibrations or psychometric questionnaire to change the energy and work-style dimensions
• Dismiss matches with a reason and rate match quality — this trains your weights

Limitations we know about

AI profile extraction can misread a CV — that's why corrections override it. The semantic similarity models are built by third parties on data we cannot inspect, so we test our score distributions for disparities across cohorts (for example, people with career gaps) on a recurring basis and publish the method in our engineering documentation. Testing reduces risk; it cannot prove the absence of bias. Treat every score as a starting point for your own judgement, especially when the confidence figure is low.

Your data rights

You can export everything we hold about you (including every match score and its explanation) or delete your account and data at any time. Questions: privacy@intothe.zone.

We are preparing intothe.zone for the EU AI Act's requirements for employment-related AI. This page is part of that transparency work; it is a plain-language disclosure, not a certification of compliance.