AI-Powered Candidate Shortlisting Automation
Automatically shortlist and rank applicants inside ERPNext so hiring teams in education act faster on top candidates.
Trusted by
Built on proven NLP + LLM methods used in academic admissions and institutional pilots; integrates natively with ERPNext HR modules and standard workflow tools.
Success Story
Hassan II University processed 2,325 CVs, averaging 3.84 seconds per CV using an NLP CV-processing pipeline (example of a comparable NLP approach, not this agent).
Integrates with
Problem
Education HR teams and admissions offices receive high volumes of CVs and job applications but lack capacity for consistent, fast triage. Manual screening is slow, inconsistent, and creates delays in hiring or onboarding faculty/staff.
Solution
This agent automates triage: it parses resumes uploaded to ERPNext, extracts structured fields (education, roles, dates, skills), scores and ranks candidates against role criteria using an LLM-assisted scoring prompt, writes shortlist statuses and reviewer notes back into ERPNext, and triggers interview workflows for flagged candidates.
Result
Faster time-to-shortlist, consistent candidate ranking, fewer administrative hours spent on triage, and a reliable audit trail inside ERPNext for compliance and reporting.
Use Cases
Universities, colleges and training providers receive many applications for academic and administrative roles yet often lack bandwidth for consistent, fast shortlisting. This agent connects to ERPNext’s Recruitment DocTypes, ingests resumes (PDF/DOCX), uses an NLP pipeline (entity extraction + GPT-style contextual scoring) to extract education, experience, skills and match them to job requirements, then writes a ranked shortlist and structured notes back into ERPNext. Recruiters review pre-ranked candidates, apply custom thresholds, and export shortlists to interview scheduling. The workflow reduces manual triage, enforces consistent evaluation across roles, preserves an auditable decision trail inside ERPNext, and scales for peak hiring seasons or large admissions-related recruitments.
Integrations
Connect to your existing tools seamlessly
Technology Stack
Automation
Automation
Infrastructure
Implementation Timeline
Define Role Criteria & Output Schema
0.5 dayagree required fields, scoring weights, and shortlist labels; create output JSON schema
Connect ERPNext Uploads & Workflow Trigger
0.5 daywire ERPNext job application uploads to webhook or watch folder
Develop Parsing Prompts & Scoring Logic
1 daycraft LLM prompts and NER pipelines; test on sample CVs
Integrate Scoring → ERPNext Update Pipeline
0.5 daymap parsed fields and scores to ERPNext candidate DocTypes; add notifications
Pilot, Validate & Refine
0.5 dayrun on real applicant batch, refine thresholds, finalize auditing rules
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