Talentino ranks applicants against the role, quoting the resume lines its grades rest on. Missing a notice period? Request it by email or WhatsApp, and the answer lands in the profile, next to their interview questions.
Free to start, no credit card required. Free tier + pay-as-you-go credits What a credit buys
Talentino grades each applicant on every requirement, quotes the resume lines its grades rest on, and ranks the applicants. You build the shortlist.
Paste or upload the job description. Check the requirements Talentino lists, mark the deal-breakers and set their weight. Save them as a template for the next role.
Analyze Job Offer reads a pasted or uploaded offer, lists its issues by severity and proposes fixes.
Requirements and screeningUpload files or folders in bulk, or add people from your talent pool. Application forms and career pages bring new applicants into the same database, with their recorded video and voice answers to play back.
Ways to bring candidates inRead the ranking, each candidate’s strengths and concerns, and the resume evidence the grades rest on. Compare finalists, build your shortlist and export a scoring report as a PDF.
Scoring and comparisonEvery candidate is scored on the same requirements, with the same weights. Open a requirement to see its grade and the resume line it rests on, then read the career around it.
How careers and skills are read
Put two to four candidates side by side, requirement by requirement, then read Talentino’s written comparison. The shortlist stays your call.
Candidate comparisonBoth meet the core operations requirements. They differ on the size of team they have led and on certification.
Candidate A: the certification, and a longer run in operations.
Candidate A has led 12 people, not 20. Candidate B has no project management certification.
Whether A’s two-site management carries to three sites. Candidate B has led the larger team.
Choose the details and the candidates, then send one request by email or WhatsApp. Each reply updates that candidate’s profile, with its source and time, so an answer can be waiting in the profile before you call.
Talentino fills your template with the missing details. You review and send the email. The candidate replies, and the answers are added to their profile.
You start the request. Talentino sends its approved opening message, then an assistant asks for the selected details.
The Conversations tab shows what was asked, what came back and the exchange itself. You can pause the assistant and write to the candidate yourself. Each answer lands in the profile with its source and time.
Once a candidate is scored, Talentino writes their interview questions, aimed at the requirements their resume supports least.
Talentino explains why it suggests each question. Add your own, or include up to five in your next request to the candidate.
You led 12 people across two sites at Samplefield; how would you lead 20 across three?
The role calls for a team of about 20 across several sites; the resume describes 12 across two.
Candidates stay in your talent pool with their resume, answers and history. Search it in plain language and add past applicants to a new role.
Candidate B first applied for a Warehouse Supervisor role. A plain-language search found the profile again, and you added it to this one.
Search and talent-pool features
Everyone on the team reads the same profiles and the same evidence.
There is a free tier and no credit card is required to start. Beyond it Talentino is pay-as-you-go: AI actions are priced in credits, and you confirm the exact cost of a scoring run before it starts.
Talentino does the reading. It processes the pile and produces a first-pass analysis with the explanation attached, and the scores and rankings it produces are advisory. Shortlist and reject decisions are applied from the candidate review screen with the cited evidence in view, and each status keeps a record of who applied it.
The application and file storage run on AWS in Frankfurt (eu-central-1). Those two components are named deliberately: model inference runs on third-party AI providers, and we do not extend the Frankfurt statement to cover them.
In the app: the role's weighted criteria, per-requirement grades with citations from the resume, the score and the weighting behind it, and the audit trail. Each status keeps a record of who applied it, and because the criteria and the weighting are fixed on the role and stored with it, a past decision can be re-run and checked against the same standard. The PDF export is narrower: every requirement scored out of 100 and grouped by how well it was met, each with the scoring explanation, deal-breakers flagged, and the overall score with its summary, strengths and concerns. The citations, the weighting and the status history stay in the app.
All you need is a job description and the resumes you already have.
Prefer a demo? We show you screening and candidate requests on a sample role.
The product views on this page are illustrations: recompositions of Talentino’s interface with fictional sample data, not a recorded customer run.