SelektaScreen smarter.
Hire faster.
Selekta reads every CV, scores every candidate against your role the same way every time, and gives your HR team a ranked shortlist in minutes instead of days.
Manual CV screening doesn't scale
Every open role brings a flood of CVs. Reviewing them by hand is slow, inconsistent, and puts your best candidates at risk of slipping through, or losing them to a faster competitor.
Hours per requisition
HR teams spend hours manually reading and comparing CVs for every single role.
Inconsistent judgment
Two reviewers score the same CV differently; there's no shared, repeatable rubric.
Top talent gets lost
Strong candidates sit buried in the pile while slower response times lose them elsewhere.
No visibility
Leadership can't see pipeline health, hiring velocity, or where roles are stuck.
Four steps, one upload
You do step one. Selekta does the rest and tells you when it is finished.
Upload a batch
Drag in every CV for the role at once. PDF only, so nothing weird slips into the pipeline.
Extract
OCR pulls the text off the page, then structured fields come out: contact, experience, education, skills.
Evaluate
Each candidate is scored against your job description on three dimensions, with a written verdict.
Shortlist
Sort, filter, move candidates through the pipeline. Rejections and invites go out on your rules.
How a score becomes a decision
Every candidate lands in a band. The band is what your team actually acts on, and it is calculated the same way every single time. Move the slider.
One place the whole hire lives
Stage changes are logged with who did it and when. Nothing moves silently.
See it run on your own CVs
Bring a real job description and a stack of real applications. Thirty minutes is enough to know whether this fits your team.
calendar_monthBook a walkthroughWhat you get
Everything below is in the product today, not on a roadmap slide.
Batch screening
Upload the whole applicant pile in one go. Fifteen CVs process at a time and a bad file never stalls the rest of the batch.
Multi-dimensional scoring
Related Skills, Experience Level and Education, each 0 to 100, equally weighted into one overall score. No hidden weighting to argue about.
Written verdict
Every score comes with a one-sentence justification and a summary, so a hiring manager can see the reasoning instead of a bare number.
Candidate database
One person, many applications. Search across every role you have ever posted and see a candidate's full history in one view.
Rule-based candidate email
Set a rule per stage, with a delay in business days. Weekends are skipped and mail only goes out inside working hours.
Auto-reject threshold
Set a score floor per job. Anything under it is rejected on arrival, logged separately from manual decisions, and never touches a candidate you already moved forward.
Interview questions
Generate questions tailored to the gaps in a specific candidate's CV, on demand, and reuse them at the interview.
Excel and PDF export
Take the shortlist to a meeting in a format everyone already opens. Every export is recorded in the audit log.
Audit trail
Stage changes, exports, deletions, logins. Who did what, when, from where, kept for when someone asks.
Ready to see it on real CVs?
We will run your own applications through the pipeline and walk you through the output.
rocket_launchRequest a demoWhere candidate data lives
Screening CVs means handling personal data. Here is the honest version.
Residency
Application records, CV files and extracted candidate data are stored on cloud infrastructure in Jakarta, Indonesia. Text recognition runs in Singapore because that capability is not offered in the Jakarta region.
Consent
Candidates applying through a public careers page pass an explicit consent gate before a CV is accepted. Consent is recorded with a timestamp on the application.
Retention
Applications and their files are deleted automatically twelve months after the last activity on them. Deletion removes the stored file, not just the database row.
What a candidate can ask for
- A copy of the personal data held about them
- Correction of anything recorded incorrectly
- Erasure of their application and CV file
- Withdrawal of consent, which triggers erasure
What the AI does and does not do
An AI model reads the CV text and produces scores plus a written justification against the job description. It does not make the hiring decision. A person moves every candidate between stages, except where your own team has configured an automatic rejection threshold, and that action is logged distinctly so it is always visible as automated.
Rejection notices
A rejection email never discloses a score, a ranking or an AI-generated reason. Candidates are told the outcome, not the internal assessment.
Access control
Every record is scoped to one company. Administrator-only actions, including screening rules and thresholds, are enforced on the server, not hidden in the interface. Database connections are encrypted and certificate-verified.
Let's talk
Tell us the roles you hire for and roughly how many CVs land per opening.