Questions and answers

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.

Yes. Talentino parses resumes in many languages and detects the candidate's language automatically, and outreach emails warn you when languages differ. The interface itself ships in English and French.

Yes. A shared talent pool, candidate notes, activity tracking and role-based permissions are built in, so the whole hiring team works from the same evidence.

Every score is built the same way: requirements extracted from your job description, each one graded against the resume, with the supporting lines quoted so you can check the judgment yourself. Talentino is a decision-support tool: the scores and explanations are advisory, and the evidence is on screen for you to check before you decide. And the engine is deterministic by design: the same criteria and the same weighting are applied to every candidate, so what you check is one standard rather than a fresh opinion per resume.

See the full argument

It is built to augment recruiters, not replace them. The platform automates processing and first-pass analysis with transparent explanations, 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.

Yes. Adjust the weighting for skills, experience and qualifications (emphasize soft skills for managers, technical depth for engineers) and define must-have versus nice-to-have criteria, down to hard deal-breakers.

Three ways: evaluation focuses on objective skills and experience extracted consistently; the same criteria are applied uniformly to every candidate for a role; and every score carries a transparent explanation you can review and challenge.

Resume files are encrypted in transit and at rest. Every record carries the customer account it belongs to, and every request is scoped to that account. Access is governed by role-based permissions, and safeguards against manipulation attempts like keyword stuffing are built in.

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. Bring the question to a demo call and we will go through the components involved.

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.

Start with the privacy policy, then bring the specifics to a demo call. That is where we go through where the data runs, which components are involved, how candidate files are handled, and what you can export if a decision is challenged.

Read the privacy policy (draft, under counsel review)Where the data runs