Every scorecomes with receipts.
Every score. Every requirement. The evidence behind it. Open any score and each requirement is graded, with the resume line that earned it quoted in full. The rest of this page shows what the engine does with that evidence.
Free to start, no credit card required.Sixty seconds, the whole story.
Evidence you can show.
Every score decomposes into per-requirement grades, and every grade quotes the resume lines behind it. When a hiring manager or a client asks “why this one?”, you show the evidence, not a gut feel. The citations live in the app, where you open a score; the exported PDF carries the requirement scores, the scoring explanations and the summary.
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Quoted from the resumeFour things it does after the score.
The comparison, the pool, the career read, and the request for what is missing.
It makes the case, not just the ranking.
Put two to four candidates side by side and Talentino writes the comparison: where each one is stronger, where each one is thinner, and which one the requirements point to. You get an argued write-up, not a table you have to interpret yourself.
The database is yours, and it compounds.
Every candidate you evaluate or capture stays in a database scoped to your account, searchable in plain language for the next role you open. The work you put into one search is still there for the next one.
Every past role, classified against this one.
Each position in the work history is tagged as a direct, partial, or unrelated match for the role you are hiring for, with the reasoning attached. It is read alongside tenure and the gaps between roles.
It tells you exactly what is missing.
When a profile is incomplete, Talentino identifies which fields are actually missing and prepares a request for precisely those. The message is a template with the fields filled in: you choose the recipient, read it over, and send it yourself.
Built to score the same resume the same way.
The criteria, the weighting and the evidence are fixed by the role, not re-invented for each request. Re-prompt a general-purpose AI assistant and it reasons fresh each time; the number drifts.
What “deterministic” means, in plain words.
Deterministic is a property of how the engine is built: your criteria and your weighting decide the score, applied the same way to every candidate, instead of being re-invented for each request. No mood, no “it depends when you asked.”
That is what makes a ranking something you can inspect, compare across weeks, and audit.
Why not just paste resumes into a general-purpose AI assistant?
You've seen how the score is built and the evidence cited. Here's the whole difference, row by row.
The checks that run before a score exists.
Safeguards against manipulation like keyword stuffing and prompt injection, so scores reflect genuine qualifications.
AI document validation runs before analysis, on by default, to catch unreadable or non-resume files before they reach the scoring engine.
Check it yourself.
Run a real role through it and see every score explained. Start free, no credit card required.