Tariq Shaban
Co-Founder & Product & Innovation Director
Organizational psychologist. Sixteen years across the Middle East, North America and Asia-Pacific. Built the way we make assessments.
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Miraai · Assessments built for the job
Most assessments are built around generic jobs, so they tell you little about the people in front of you. We build yours from your own job descriptions and the situations your teams actually face, ready in weeks. Candidates finish it, and you can show how every score was reached.
01 The problem
Off-the-shelf assessments are built around the average version of a role. They describe people, but they say little about who will do well in the role. Building your own used to mean six figures and at least six months, so most organizations never invested in one. We build yours in weeks, from your job descriptions, your performance reviews and the situations your people actually face. Once it is live it screens thousands of applicants in days. Psychologists still make every judgment call. What changed is the slow work behind them.
The standard assessments are priced per candidate. A test built for your job is a fixed fee, quoted before we start, and runs on the same per-candidate basis once it is live.
Other vendors use AI to cut time and cost. We use it to do more science, and to rebuild assessments properly.
02 Personality
Instead of a page of statements to agree or disagree with, candidates see illustrated scenes and pick between two options that are both reasonable. Neither option is the obviously right one, so there is no obviously right answer to aim for, and what comes back is closer to how they actually work. It takes under twenty minutes on a phone, and you get a profile against the traits that matter for the role, including the ones that only cause trouble when they go too far: the careful person who never quite hands work in, or the confident one who stops listening.
03 Judgment
We film short scenes from situations your own people described: the difficult customer, the shift that goes wrong, the moment a decision lands on someone. The candidate watches from the inside and chooses what they would do. They find out what the work is really like before they accept, which means fewer people leaving in the first few months, and you find out how they would handle it before you hire. Everything comes from your material, and no step moves on until a person has approved it.
04 Reasoning
Most tools try to catch cheating after it happens. We built one where it is not worth the trouble. The question stays on screen only while the candidate holds it there. Let go to pick up a phone or open another tab and it disappears while the clock keeps running. Working it out is simply faster than looking it up, so people stop trying. Run it on its own, or add facial validation and AI video proctoring on Podium365 when you also want to rule out a stand-in or a helper.
05 Proof, and what happens after
AI does the slow part of the build, drafting and screening thousands of questions before a candidate sees one. Every assessment is still tried on real people before it counts for anybody, and the whole build takes weeks rather than months.
Every enterprise client gets a psychologist and a client director by name. They are responsible for keeping your assessments and scoring models current as roles and workforces change, and for making sure your hiring teams get decisions they can use and your candidates get an experience worth their time.
06 The people
Three founders. The people who build your assessment are the people you meet, and they stay with it after it goes live.
Co-Founder & Product & Innovation Director
Organizational psychologist. Sixteen years across the Middle East, North America and Asia-Pacific. Built the way we make assessments.
Co-Founder & Commercial Director
Organizational psychologist. Nearly thirty years in recruitment and talent systems. Ran a national scholarship program of more than 15,000 applicants.
Co-Founder & Technical Director
Chartered Psychologist and technologist. Founder of Podium. Co-author of multiple assessments. Five years evaluating machine learning outcomes at Microsoft.
Next step
We'll build the first scene for it and show you, so you can look at the real thing instead of reading about it.