Full-application reading and scoring
Every application is read in full, turned into structured fields, and scored against the criteria you set. The system is designed to evaluate the whole pile rather than skipping straight to shortlisted names.
AgentR
AgentR is a hiring assistant that reads applications, verifies candidate claims, and interviews qualified applicants without calendar back-and-forth.
Overview
AgentR is a hiring assistant that reads every application, checks what candidates actually claim, and interviews the ones who clear your bar. It is built for teams that want the candidate pile read, scored, and ranked before anyone spends time on a conversation.
The product combines resume parsing, claim verification, structured screening questions, and asynchronous interviews. Rather than auto-rejecting applicants, it keeps the full pile visible, adds evidence to each judgment, and leaves the final hiring decision with the team.
Core capabilities
Claim verification with evidence
Candidate claims are checked against public sources and the candidate's own history. Each criterion can come back with a verdict, a short quote, a source reference, and a confidence figure.
Written screening questions in the candidate's words
Applicants answer your screening questions exactly as written, and those answers are scored together with the resume. The product says there is no rephrasing step and no generated question on its behalf.
Ranked shortlists with supporting context
Shortlists are ranked rather than trimmed, so the team can see the full ordered pile and review the evidence behind each placement. Repeat applicants can also be flagged across roles.
Self-serve interview scheduling
Interview invitations are triggered automatically once a candidate clears the role's bar. The interview runs without calendar sync, uses a time-limited link, and can fall back to WhatsApp for delivery.
Interview integrity monitoring
Two monitoring layers can watch the interview for room and machine signals such as suspicious camera setup, extra tabs, second displays, or capture tools. The source says these markers are attached for review and do not change the score on their own.
Where AgentR fits
High-volume applicant screening
Use it when a role attracts enough applicants that manual review becomes the bottleneck. AgentR reads the full pile, scores it against your criteria, and surfaces an ordered shortlist with evidence attached.
Claim verification before interviews
Use it when the hiring team needs to check whether candidate claims hold up before interviews. The product extracts claims from resumes, searches public sources, and marks each one with a supported verdict.
Asynchronous pre-interview screening
Use it when you want standardized screening questions without back-and-forth scheduling. Candidates answer the questions in their own words, then clear candidates receive a self-serve interview link.
Evidence-led shortlist review
Use it when you want to preserve visibility into the full candidate pool instead of cutting the list down too early. The product keeps ranked candidates available, including weaker matches, so reviewers can inspect the evidence and decide where to stop.
Repeat-applicant review
Use it when repeat applicants need to be compared across roles. The pricing page notes that repeat applicants are flagged across your roles, which can help teams notice duplicate submissions or changing histories.
Pros and Cons
Pros
- Reads every application in full instead of sampling or keyword-scanning.
- Attaches evidence, quotes, and verdicts to claims so reviewers can inspect the reasoning.
- Supports structured screening questions and asynchronous interviews without calendar coordination.
- Keeps the shortlist ordered rather than hiding lower-ranked candidates, which preserves visibility into the full pool.
- Shows plan validity and remaining credit in the product, so usage is not hidden behind a sales conversation.
Cons
- The source says it currently reads PDF files only, not Word files, scans, or links.
- There is no auto-reject stage; the product ranks and recommends, but people still decide who moves forward.
- Credit is metered against AI work, so heavier roles with more applicants draw down the balance faster.
FAQ
Does AgentR reject candidates automatically?
AgentR is set up around a candidate-to-review workflow rather than an auto-reject pipeline. It reads applications, checks claims, and can invite candidates above your chosen threshold into a structured interview, while the final decision stays with your team.
How does pricing work to get started?
The pricing page says free credits start with no card. The product also shows plan validity, credit remaining, and status in settings, and the free tier includes a full end-to-end run on a real role.
What file types does it read?
The source describes a PDF-only application intake for now. Resumes are read from PDF, not Word files, scans, or links.
How does scheduling work?
Candidates receive an interview link by email, with WhatsApp listed as a fallback. The interview is taken on their own time, without calendar sync or slot booking.
What outputs does the hiring team see?
The product returns scored criteria, verbatim evidence quotes, claim verdicts with sources, ranked shortlists, and interview recordings or transcripts. It also shows what was flagged and why, rather than hiding the reasoning behind a single score.
Quick Facts
- Category
- Hiring assistant / recruiting automation
- Platform
- Web product
- Primary users
- Hiring teams and recruiters
- Source domain
- agentr.global
- Pricing model
- Free credits to start, then more credit by agreement
- Workflow
- Read applications, check claims, shortlist, and interview qualified candidates
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