Savira/001
Savira NexHire

AI Recruitment Intelligence

An AI hiring copilot for recruiters.

Savira NexHire turns a job description into a ranked, explainable shortlist — parsing resumes, scoring candidates against your rubric, and drafting interview questions.

Not a keyword filter. A multi-agent system that reads the role, reads the talent, and shows its reasoning at every step.

I — Architecture

A hiring pipeline, not a resume parser.

A JD and a stack of resumes enter NexHire. Agents parse, evaluate, and rank — the recruiter sees a shortlist with the reasoning behind every score, and can ask follow-ups in plain English.

Input

Role + candidates

  • Job description
  • Resumes (PDF / DOCX / text)
  • Hiring rubric
  • Recruiter feedback
NexHire

Recruitment agent system

  • JD analysis agent
  • Resume intelligence
  • Evaluation + ranking
  • Recruiter copilot
Output

Shortlist + reasoning

  • Ranked candidates
  • Score + strengths + gaps
  • Interview questions
  • Explainable decisions
II — Modules

Six modules. One hiring agent.

M—01

Job Description Intelligence

A JD is a structured hiring spec, not a wall of prose. NexHire extracts the criteria recruiters actually screen against.

  • Required vs preferred skills, separated
  • Experience, education, and tech stack
  • Role responsibilities as screening criteria
  • Years of experience + seniority inferred
M—02

Resume Intelligence Engine

Resume in, structured candidate profile out. Works on PDF, DOCX, and pasted text — fields are normalized across formats.

  • Personal info, contact, location
  • Skills, projects, work history, education
  • Certifications and technical achievements
  • Stable candidate identity for ranking
M—03

Candidate Evaluation Agent

Compares each candidate against your JD on six dimensions — not just keyword overlap, but actual fit.

  • Skill match against required and preferred
  • Experience relevance + recency
  • Project similarity and tech alignment
  • Career progression + requirement gaps
M—04

Hybrid Ranking System

Semantic similarity, skill matching, LLM reasoning, and experience weighting — fused, not picked from one.

  • Vector similarity for concept-level match
  • Skill overlap as a hard signal
  • LLM-as-judge for nuanced fit
  • Recruiter feedback re-weights future rankings
M—05

Recruiter Copilot

Ask the shortlist why. Ask it to filter. Ask it to draft. Natural-language control over the ranked pipeline.

  • Why was A ranked over B?
  • Show candidates with strong ML experience
  • Which candidates lack AWS?
  • Generate interview questions for the shortlist
M—06

Multi-Tenant Enterprise

Each company is isolated at the storage layer. Roles, jobs, candidates, and evaluations never cross tenants.

  • Per-tenant data isolation
  • Role-based access on every query
  • Audit trail: who asked, what was returned
  • Dedicated tenancy available for regulated hiring
III — Hiring pipeline

How a job req becomes a shortlist.

  1. 01

    JD intake

    Parse the role into required and preferred signals.

  2. 02

    Resume parsing

    Convert each resume into a structured candidate profile.

  3. 03

    Match scoring

    Score every candidate on six fit dimensions.

  4. 04

    Reasoning

    Surface strengths, gaps, and the 'why' behind each score.

  5. 05

    Ranking

    Combine similarity, skills, and LLM judgment into a single order.

  6. 06

    Copilot handoff

    Shortlist plus a recruiter agent that answers follow-ups.

IV — What ships

Features that make NexHire sellable.

F—01

Job Description Studio

Paste a JD, get a screening spec.

F—02

Candidate Shortlist

Ranked, explainable, ready to review.

F—03

Interview Question Drafter

Role-specific questions, on demand.

F—04

Rubric + Scorecard

Consistent evaluation across panels.

F—05

Hiring Analytics

Funnel, time-to-hire, and quality.

Not a keyword filter. An AI recruitment employee.

NexHire understands the role, evaluates the talent, and explains every decision — so your hiring team spends time on people, not paperwork.