Automate Resume Screening. Shortlist Top Talent Instantly.
Skip the manual resume sift. Leverage privacy-first generative AI models to semantically align and score applicant resumes against your specific job criteria without sending sensitive candidate profiles to public cloud APIs.
The High Cost of Manual Resume Sifting
Relying on HR teams to read through hundreds of candidate PDFs wastes hundreds of work hours, delays talent acquisition, and introduces unconscious bias.
The Resume Avalanche
High-volume job postings pull in hundreds of unqualified applications. HR departments waste valuable screening hours separating top talent from noise.
Inconsistent Screen Quality
Tired recruiters scanning resumes for keywords miss qualified non-traditional profiles. Legacy ATS tools rely on exact string matches, rejecting top candidates.
Candidate Data Leakage
Uploading candidate CVs (which contain private phone numbers, emails, addresses, and compensation histories) to public cloud LLM APIs poses GDPR violation risks.
How Screening Automation Works
Our local AI system extracts profiles and aligns them against job description criteria, performing semantic ranking securely inside your local network database.
Resume Upload
Candidate PDF or Docx files are ingested directly into the secure portal database. No personal detail elements are stripped or uploaded externally.
Semantic Matching
A locally hosted Large Language Model processes candidate details, comparing career timelines and skill capabilities directly against the job requirements.
Ranked Candidate Shortlist
The screening portal outputs a structured applicant list sorted by alignment score, including short reasoning tags for recruiters.
Want to test recruitment AI with your own candidate pools?
Send us 5 sample resumes (with candidate names removed if preferred) and we will return an AI ranking report using your custom target criteria.
Request a Free Candidate Ranking ReportBuilt for Modern Talent Teams
Our generative AI platform fits directly into corporate recruitment cycles to automate screening workflows.
High-Volume Staffing
Process and filter thousands of resumes automatically for entry-level positions, internships, or mass hiring drives.
Internal Mobility
Scan your internal employee database semantically to identify qualified internal candidates whenever new roles open.
Niche Sourcing
Identify specific engineering or specialized capabilities across vast applicant pools, looking past plain synonyms.
Candidate Archiving
Auto-tag historical resumes in your archive database, making them searchable for future openings with semantic filters.
HR Automation Capabilities
Absolute Data Ownership
By hosting the matching LLM locally inside your servers, candidate contact details and salary data never leave your firewall to hit public APIs.
Contextual Understanding
The semantic matching model goes past basic keyword checks. It reads work experience details to understand the applicant's real expertise level.
Simple ATS Connections
The parser outputs clean JSON payloads including scores and justifications, mapping natively into modern ATS databases or custom hr pipelines.
{
"candidate": {
"id": "CAN-90281",
"role": "DevOps Engineer"
},
"evaluation": {
"alignment_score": 92,
"match_verdict": "highly_recommended",
"justification": "9+ years managing local Kubernetes clusters and CI/CD pipelines directly aligns with DevOps specification."
},
"missing_skills": [
"Pulumi IaC"
],
"timestamp": "2026-07-03T10:31:02Z"
}Frequently Asked Questions
Quick answers about our local generative AI resume screening capabilities.
The local Large Language Model reads candidate career summaries, project logs, and skill layouts contextually. It understands semantic synonyms, identifying that an applicant with 'Infrastructure automation' fits a DevOps role even if the exact string 'DevOps' is missing.
Yes. The matching engine runs entirely inside your virtual private cloud (VPC) or local corporate servers. Candidate files and personal contact details are never sent to third-party cloud AI vendors.
The resume parser supports standard PDF, Docx, RTF, and plain text formats directly.
Yes. The screening platform outputs standardized JSON matching packets, integrating natively with custom corporate ATS platforms or database connectors.
Yes. You can define specific weighting parameters, mandatory certifications, minimum experience durations, and custom questions for each job posting to refine the AI's scoring rules.
Deploy Your Private Talent Screener
Shortlist top candidates automatically while protecting data residency. Talk to our AI team about integration.