Teenva AI & Digital Ventures builds AI recruitment screening for HR teams, staffing firms, IT services recruiters, and high-volume hiring programs from Bangalore, India. Upload resumes or pull applicants from your ATS—Teenva parses skills and experience, matches each candidate to the job description, returns a ranked shortlist with explainable fit reasons, and syncs status to Zoho Recruit or your custom HR app—with human recruiters making every hire/reject decision.
Keyword filters miss qualified candidates; opaque auto-reject tools create compliance risk. Teenva is decision-support: no automated rejection without recruiter review, protected attributes excluded from models, and audit logs for fairness reviews.
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AI recruitment screening—JD match scores, explainable shortlists, and ATS sync with bias-aware controls.
Hub: AI solutions · Domain: HR
What recruiters get
| Output | Description |
|---|---|
| Match score | 0–100 fit to your JD requirements |
| Ranked list | Sort by score, recency, or custom weight |
| Fit summary | Bullet reasons: skills met, gaps, years experience |
| Skill extraction | Structured tags from resume (Python, GST, B2B sales, etc.) |
| Knockout flags | Missing must-haves (visa, location, certification) via rules |
| Duplicate detection (scoped) | Same candidate applied twice |
| Bulk upload report | 500-campus PDFs → parsed table in minutes |
| Interview questions (scoped) | Suggested questions from gaps—not auto-asked |
Screening assists recruiters—final status change is human.
How matching works
| Step | Technology |
|---|---|
| Ingest | PDF/DOCX resume, LinkedIn export (scoped), ATS webhook |
| Parse | OCR + layout models; LLM assist for messy formats (scoped) |
| Normalize | Job titles, dates, education, skills ontology |
| JD parse | Must-have vs nice-to-have from recruiter-entered JD |
| Score | Semantic similarity + rule weights + experience years |
| Explain | Top matching skills + top gaps cited from resume text |
| Review UI | Recruiter override score; mandatory notes on reject (scoped) |
| Sync | Write score + stage to ATS |
Ranking uses ML + embeddings + rules—not “ChatGPT hire/no hire” in one prompt.
Bias-aware & compliance controls
| Control | Implementation |
|---|---|
| Excluded features | Gender, age, religion, caste, photo inference—never model inputs |
| Blind review mode (scoped) | Hide name/university until shortlist stage |
| Consistent rubric | Same JD weights for all applicants in requisition |
| Audit trail | Score version, recruiter override, timestamp |
| No auto-reject (default) | AI suggests tier; human sets rejected |
| Regional compliance (scoped) | Align with your legal on AI in hiring (India/global) |
| Data retention | TTL on resumes per policy; encryption at rest |
Teenva builds software; your HR/legal owns hiring policy and adverse impact review (scoped).
Features we implement
Screening API
POST /jobs/{id}/candidates → score + summaryRecruiter portal
Requisition, JD editor, ranked pipeline kanbanBulk import
ZIP of resumes; async job queueATS integration
Zoho Recruit, custom ATS via APIKnockout rules UI
Location, notice period, salary band (scoped)Collaboration
Hiring manager comments; @mention on candidateAnalytics
Time-to-shortlist, source quality, override rateCampus hiring (scoped)
Batch drives for engineering/fresher intakesWhite-label (scoped)
Staffing firm client-branded portalEmployer brand hook
Job posts from social assistant UTM to applicant source tracking (scoped)
Architecture
Application (ATS, careers site, email inbox)
Resume ingest + parse → structured candidate profile
JD requirements (must / nice) + knockout rules
Match model → score + explainable drivers
Recruiter review → shortlist / hold / reject (human)
ATS stage update + interview scheduling hook (scoped)
Outcome labels (hired/rejected) → model monitoring (scoped)
- Deployment — Your VPC; resumes not used to train public models
Use cases
| Hiring motion | Screening focus |
|---|---|
| Tech hiring (India) | Skills, projects, notice period; bulk campus PDFs |
| B2B sales / CS | Industry experience, quota language in CV |
| IT services bench (scoped) | Multi-JD match across open reqs |
| Staffing agency | Client JD upload; submittal shortlist per client |
| Remote global (scoped) | Timezone and language rules |
| Internal mobility (scoped) | Match employees to open roles from HRIS export |
AI recruitment screening vs sibling HR AI
| Product | Focus |
|---|---|
| AI recruitment screening | Pre-hire resume/JD match |
| HR helpdesk chatbot | Employee policy and benefits Q&A |
| Employee analytics AI | Workforce attrition, engagement, capacity |
Different from AI lead scoring—candidates, not sales leads.
Hiring decisions stay human. AI ranks and explains—we do not auto-reject by default, and protected attributes stay out of the model.
Why Teenva AI
Recruiter-first UX
Shortlist speed without black-box anxietyIndia hiring reality
Bulk PDFs, diverse resume formats, campus drivesATS-ready
Zoho and custom HR stacksFairness by design
Exclusions, audit, override—not marketing “unbiased AI” claimsFull build
SaaS ATS module + screening in one team
Delivery process
Discovery
volumes, ATS, roles, compliance stance on AI hiring
JD taxonomy
must-have skills, knockouts, scoring weights
Resume sample audit
parser accuracy on 100 representative CVs
Pilot requisition
one role; recruiter feedback on explanations
Bias review
exclude fields; document rubric with HR
ATS integration
bi-directional sync
Bulk import
campus or drive campaign (scoped)
Training
recruiter playbook for overrides
Monitor
override rate, time-to-shortlist, hire correlation (scoped)
Explore
Frequently asked questions
Default no—AI ranks; recruiter rejects with optional required reason.
No tool guarantees that—we exclude protected attributes, use consistent rubrics, and log overrides; your HR runs fairness reviews.
Yes—multi-column, project sections, CGPA, diverse degree names (scoped tuning).
Yes via Zoho integration (scoped to products you license).
ZIP upload + async scoring + export shortlist (scoped).
No—structured parse + match + explain; LLM assists summary only.
Hosted in your environment; retention TTL configurable; DPDP alignment (scoped).
Multi-tenant client JDs and branded portal (scoped).
Route to HR helpdesk chatbot.
8–12 weeks MVP—parser, score, recruiter UI, one ATS integration.
Related HR AI solutions
Build your AI recruitment screening system
Resume parsing, JD match scores, explainable shortlists, and ATS sync—with bias-aware guardrails.
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