Kliv

    Recruitment & Hiring Management

    Build an AI-powered video interview platform

    Kliv is an AI app builder. Describe your interview kits, candidate links, upload limits, reviewer rules, scorecards, and emails, and it builds the video interview platform.

    kliv.dev

    Just enter your idea into the text box and AI will build it for you

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    What is Kliv?

    Kliv isn’t a hiring subscription with a fixed workflow — it’s an AI app builder that builds software for you.

    You describe the app you need in plain words, and Kliv builds it: the database, candidate rooms, file handling, scorecards, pipeline states, emails, permissions, and admin screens. What you get is a real web app that’s yours, live on your own domain, and you can keep changing it by asking for changes.

    On this page, that app is an AI-powered video interview platform. Kliv builds all kinds of web apps; hiring tools are one example.

    Why build your own video interview tool?

    Phone screens drift. Questions change by the fifth call, notes get thinner, and candidates meet different versions of the same interview. Enterprise screening tools can be too expensive or shaped around someone else’s pipeline.

    Kliv builds the tool your process needs: role-specific question kits, private candidate uploads, a shared rubric, signed scorecards, and pipeline emails driven by state.

    Kits, takes, scorecards: the anatomy of one opening

    Screening should produce records, not scattered impressions.

    The question kit

    Five questions per role, each with thinking time and a recording limit. Kits are versioned, so the app can show which candidates answered which questions.

    The take

    A candidate’s uploaded answers, one file per question, stored privately. Assigned reviewers and the candidate can see them.

    The candidate’s room

    One private link and one login for the candidate: questions, deadline, and submitted takes. Other candidates do not exist from inside that room.

    The scorecard

    Your rubric as rows: criteria, scale, and required comments. Every score is signed by its reviewer and timestamped.

    The pipeline states

    Invited, submitted, under review, advanced, declined. Each candidate sits in one state, and the state decides which emails send and which pages exist.

    An example: Damaris’s support-team hiring

    Here’s how one hiring team might use it. It’s only an example — you would describe your own roles, reviewers, and score rules.

    01

    The role gets a locked question kit

    Damaris writes five support-team questions, sets 90 seconds of thinking time and three minutes per answer, and locks version two of the kit.

    02

    Candidates get private links

    Forty candidates receive links and a one-week deadline. Invite emails, day-five nudges, and deadline reminders send from the same pipeline mechanism.

    03

    Uploads land in a reviewer queue

    Candidates record when their time zone allows. Each video file lands under the candidate’s row, so reviewers work from the app instead of email attachments.

    04

    Reviewers score before seeing each other

    Tessa and Yusuf score independently on the same rubric. Neither sees the other’s numbers until both have signed, and large disagreements are flagged.

    05

    The shortlist has evidence attached

    The final shortlist is three names with scorecards and videos attached. Advances and declines are state changes, not manual Friday tasks.

    Describe what you want to build

    Kliv builds from your description, so the more detail you give, the closer the first version. Describe roles, question kits, time limits, retake rules, reviewer rules, and candidate emails. Here are three to build on:

    kliv.dev

    Support-team screening

    Question kits, timed uploads, and two-reviewer scorecards.

    “Build an AI-powered video interview platform for our support-team hiring. Each role has a five-question kit, candidates get 90 seconds of thinking time and three minutes per answer, uploads happen through private links, and two reviewers score each take independently on the same rubric.”

    kliv.dev

    Seasonal retail hiring

    High volume with store-specific review queues.

    “Build a video screening tool for seasonal retail hiring. Hundreds of candidates answer three set questions, each store manager reviews only applicants for their own location, candidates get one retake per question, and declined candidates receive an email when their state changes.”

    kliv.dev

    Internal promotions panel

    Fixed panel kit and blind first scoring.

    “Build an internal interview tool for team-lead promotions. Employees record answers to a fixed panel kit, a three-person committee scores without seeing each other’s notes until all have signed, and HR keeps the final record with retention rules.”

    The quiet parts of a loud decision

    Videos are files with rules. Interview video is personal. Each file is scoped to its candidate and the reviewers assigned to that requisition, with a real wall between candidates and between hiring managers on different roles.

    States drive the emails. Invitation, nudge, received receipt, advance, and decline are your templates. They send when the pipeline state changes and are logged when they send.

    The assistant handles logistics, not judgment. Candidates ask about deadlines, format, and retakes. An assistant in the candidate’s room can answer from your process notes and that candidate’s own rows. Anything outside those rules goes to a human.

    Every team eventually meets a process too specific to buy software for. Hiring was yours today; what teams build for themselves covers the rest.

    Common questions

    What exactly is Kliv?

    Kliv is an AI app builder that creates custom web apps from a description. For video interviews, it builds question kits, candidate rooms, video uploads, scorecards, reviewer permissions, emails, and admin screens.

    Do I get a real app, or a template?

    A real app. Kliv builds around your roles, question kits, candidate flow, reviewer rules, scorecards, and retention policy.

    Can I change it after it’s built?

    Yes. You can change kit rules, add roles, revise emails, adjust retakes, or add another review step later.

    Does the AI score candidates?

    No. Scores come from named reviewers against a rubric you wrote. The AI builds the app, and an in-app assistant can handle candidate logistics.

    Who can watch a candidate’s takes?

    The candidate and assigned reviewers for that requisition. A hiring manager on another role does not have a route to those files.

    Can candidates re-record an answer?

    Your call, per kit. You can allow one retake or none, and the policy is enforced the same way for every candidate in that kit.

    What happens to videos after a role closes?

    Whatever retention rule you set. A scheduled job can delete files after a fixed number of days, or keep them with the hiring record.

    Can reviewers score independently first?

    Yes. You can require reviewers to sign before they see each other’s scores, then flag large disagreements for discussion.

    Can pipeline emails send automatically?

    Yes. Invites, nudges, receipts, advances, and declines can send from your templates when candidate states change.

    Can I use my own domain?

    Yes. The interview platform can run on your own domain and go live as soon as you build it.

    Can I move off Kliv later?

    Yes. The code syncs to your own Git repository, so leaving is a git pull, not a rebuild.

    Do I need a separate applicant tracking system?

    Not for the workflow described here. Candidate rooms, uploads, scorecards, states, and emails can all live in the same app.

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    Show that every candidate got the same screen

    Describe the role, the questions, the time limits, who reviews, and how decisions move. Kliv builds the interview tool around that process.