Startup proposal deck
AI first interview app
A validation-first product concept for automating first-stage interviews, saving recruiters three hours per candidate, and only building after two companies commit.
First stage
Frontend Engineer
Government ID shown before interview. Recruiter can review the proof frame.
AI scorecard
01 / Recruiting bottleneck
First-stage screening is still too manual.
Recruiters spend valuable time preparing questions, scheduling, repeating first-round interviews, writing summaries, and sending rejection emails.
AI adoption is now normal in business, but HR leaders are being pushed to show measurable efficiency instead of experimentation. Gartner says HR operations are under pressure to automate service delivery and upgrade productivity.1
3h
Target time saved from every first-stage interview.
20m
Candidate completes the AI interview anytime, anywhere.
2+
Paid pilots required before implementation starts.
02 / Market signal
The timing is right, but trust is the product.
88%
Organizations using AI in at least one business function, according to McKinsey.2
45%
US workers who report using AI at work, while SHRM flags a widening HR skills gap.3
AI agents
HR buyers are moving from chatbots to workflow agents that schedule, summarize, and follow up.1
Audit
Employment AI is regulated. Bias audits, notice, human review, and documentation are part of the sale.4
03 / Product wedge
One link replaces the repetitive first interview.
Core promise
The recruiter reviews evidence, not raw scheduling chaos.
04 / Workflow
The interview agent handles the first stage end to end.
Prepare
Upload a JD, target level, must-have skills, and interview rubric.
Invite
Candidate receives a 20 minute first-stage interview link and calendar options.
Verify
Candidate shows an ID card and confirms live presence before recording.
Interview
AI asks structured questions and role-specific follow-ups by video, phone, or chat.
Score
Recruiter receives summary, evidence clips, scorecard, and recommended next step.
Act
Pass candidates move to human scheduling. Rejections get a polite automatic email.
05 / System design
A lean architecture that can start manual and become software.
Candidate experience
Interview agent
Review workspace
Trust layer
Storage: encrypted interview video, transcript, scorecard, ID proof frame, and audit log.
Integrations: Google Calendar, Outlook, email, ATS export, and later phone or messaging channels.
MVP path: automate the candidate link and review report first; keep calibration human-assisted.
06 / Agentic roadmap
Start with video. Expand into phone, email, and messaging.
Asynchronous video
Best for screening evidence, communication, and recruiter review.
AI phone interview
Best for high-volume roles, low friction, and faster candidate response.
Email follow-up
Best for invites, reminders, rejection notes, and hiring-manager nudges.
Messaging agent
Best for candidate Q&A, rescheduling, and status updates.
07 / Competitive gap
In Mongolia, the real competitors are job boards and recruiter services, not AI-native interview products.
Zangia.mn
Mongolia's largest local hiring platform and employer marketplace.6
Where they are strong
Strongest local distribution and employer mindshare for finding applicants.
Gap we can use
Built for attracting candidates, not for automating structured first-round interviews or producing evidence-based interview reports.
Worki.mn
Mobile-friendly local jobs platform with company pages, direct applications, and AI-assisted salary tools.7
Where they are strong
Modern candidate UX and visible adoption by major Mongolian employers.
Gap we can use
Application flow is the main product. Interview workflow, scoring, and recruiter-side automation are not the wedge.
Mongolia Talent Network
Recruiter-led hiring, employer branding, PEO/EOR, and premium talent services for Mongolian employers.8
Where they are strong
High-trust local service model and strong credibility with established companies.
Gap we can use
Service-heavy and human-led. Less scalable and less standardized than AI-run first-round screening.
Mongolia Talent Network on Worki
Local employer profile showing Ulaanbaatar presence and long-running recruitment operations.9
Where they are strong
Confirms deep local market presence and employer-side hiring relationships.
Gap we can use
Still a recruiter-service model, not a software-native interview layer.
Zangia ecosystem tools
Adjacent local substitutes such as Testly and training products inside the Zangia ecosystem.10
Where they are strong
Easy add-on for employers already using a familiar Mongolian HR brand.
Gap we can use
Assessments and training do not replace a full conversational interview screen with scheduling, evidence clips, and human review.
Positioning takeaway
The wedge is not "more HR software." The wedge is a Mongolia-ready interview layer that sits after sourcing, automates first-round screening, and gives hiring managers evidence instead of extra admin.
08 / Compliance by design
No black box hiring decisions. Human review stays in control.
Consent and retention
Candidates see what is collected, why, and when video or ID evidence is deleted.
Human override
AI recommends. The hiring team makes the decision and can inspect every evidence clip.
Bias audit posture
Structured rubrics, score distribution checks, and documentation for regulated buyers.
No facial emotion scoring
ID verification is for authenticity only. Avoid pseudoscientific personality claims.
EEOC guidance and local AEDT laws make transparency, job-relatedness, and bias controls a sales requirement, not a feature afterthought.5
09 / Pricing
Price per interview first. Move to subscription after proof.
Pilot
10,000 MNT / interview
Pay as you go, first 10 interviews, white-glove setup
Starter
390,000 MNT / month
50 interviews, JD templates, calendar automation, email follow-ups
Growth
1,200,000 MNT / month
180 interviews, branded portal, reviewer seats, analytics export
Agency
Custom + usage
Multiple clients, shared pools, ATS export, dedicated onboarding
Validation offer
First 10 interviews as a paid pilot with manual white-glove setup.
10 / Go to market
Sell the promise before building the platform.
01
Pitch deck
Use this page as the core story for HR managers, founders, and recruiting agencies.
02
Landing page
Create one focused page with pricing, workflow, trust posture, and a booking link.
03
5 emails per day
Target HR teams in tech, finance, education, customer support, and agencies.
04
Calendly booking
Every email and deck CTA routes to a short pilot discovery call.
05
Manual MVP
Use AI tools plus human QA behind the scenes until two companies commit.
06
Buyer proof
Track replies, call bookings, pilot conversion, objections, and time-saved estimates.
11 / Decision rule
Do not build until two companies say yes.
Success condition: two paid pilot commitments.
A commitment can be a signed pilot, prepaid interview bundle, or written buyer agreement to run a first batch after delivery.
Measure objections
Trust, candidate experience, pricing, and integration concerns.
Measure willingness to pay
Validate 10,000 MNT per interview against volume discounts.
Measure urgency
Find teams with active hiring pipelines now, not someday.
Appendix
Research notes
Market-size numbers for AI hiring vary widely by definition. The stronger investor story is not a giant top-down number. It is a narrow wedge: recruiters already feel the pain, AI is accepted in workflows, and compliance makes audited human-in-the-loop products more credible.