Screening, assessments,
and AI interviews. One pipeline.
Smartyoz runs your hiring end-to-end — from resume scoring to live AI voice interviews. Configure once, let the pipeline handle the rest.
The product
AI resume screening
Paste a job description, upload resumes in bulk. The LLM scores each candidate against your JD keywords with per-skill breakdowns. Set a threshold — top N or percentage — and move shortlisted candidates forward automatically.
| Candidate | Matched Skills | Score |
|---|---|---|
| Arjun Sharma | ReactTypeScriptNode.js | 94% |
| Priya Nair | ReactCSSGraphQL | 88% |
| Karthik Raj | VueTypeScript | 81% |
| Sneha Pillai | ReactRedux | 76% |
Technical MCQ · Q4 of 20
What is the time complexity of searching in a balanced BST?
seen = {}
for i, n in enumerate(nums):
if target - n in seen:
return [seen[target-n], i]
seen[n] = i▊
Online assessments
Technical MCQ, behavioral, aptitude — each category configured independently. Add live coding challenges with a sandboxed runner supporting Python, JavaScript, Java, C++, Go, and Rust. Candidates get a timed session. Scoring is automatic.
AI voice interviews
The AI generates questions from your JD, conducts a real-time voice conversation, asks follow-ups based on answers, and scores each response against rubrics — all in parallel so the candidate never waits. You get a scored transcript and summary.
AI Interviewer
Candidate
Two hiring paths.
One platform.
Whether you are mass-hiring freshers through a campus drive or meticulously screening experienced professionals, the pipeline adapts to your workflow.
Experienced Hiring
Resume-first pipeline
Upload JD
AI extracts skills and scoring weights
Bulk upload resumes
PDF, DOCX — parsed and indexed automatically
Run screening
LLM scores each resume semantically
Send interview invite
Candidate gets a time-limited link
AI conducts interview
Structured voice conversation, scored transcript
Campus / Fresher
Assessment-first pipeline
Create position
Configure MCQ categories + coding test
Share registration link
Candidates self-register with details
Online assessment
Timed MCQ + live coding — auto-scored
Auto-invite passed
Pipeline chains to next stage automatically
AI conducts interview
Same structured interview flow
The entire pipeline can run itself
Turn on auto-assessment and auto-invite. Candidates move from screening to assessment to interview without manual handoffs.
41%
Lower time-to-hire
3.7×
More interviews completed
99.95%
Platform uptime
Security
Multi-tenant by design
Tenant isolation
PostgreSQL RLS on every table. Tenant context set before any query.
Role-based access
Four roles: super_admin, tenant_admin, hr, candidate. Route guards enforce access.
Scoped tokens
Every invite, assessment, and registration token is tenant-scoped by design.
Audit-ready
Pipeline events, status transitions, and candidate journey tracked end-to-end.
FAQ
Create a position, paste your JD, and upload resumes. You can run an end-to-end hiring flow — screening through AI interview — on day one.
They receive a link valid for a configurable window (default 48 hours). They click, verify their mic, and the AI interviewer starts a structured conversation. No calendar booking, no scheduling back-and-forth.
Multi-category MCQ (technical, behavioral, aptitude) and live coding challenges with a sandboxed code runner. Each section is independently configurable — source questions from AI, your bank, or add manually.
Yes. Experienced hiring starts with resume screening. Campus/fresher hiring starts with a self-registration link and assessment-first flow. Both converge at the AI interview stage.
Fully. Every table has tenant_id scoping with PostgreSQL row-level security. Tokens are tenant-scoped. There's no cross-tenant data access.
Ready to stop context-switching
across your hiring stack?
Set up your first position and run a full pipeline — screening, assessments, interview — today.