Interactive demo — everything below is live and running on sample data. Nothing you do here is saved.

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Recruiter dashboard

A live snapshot of a hiring team's pipeline — the same view your recruiters get on day one.

4
Open roles
▲ actively hiring
517
Total applicants
across all roles
80
Avg AI fit score
3 strong hires flagged
21d
Time to hire
▼ 45% vs 6 mo ago
Pipeline breakdown
Applied
1
Screening
2
Interview
4
Offer
1
Hired
1
Rejected
1
Upcoming & recent interviews
CandidateRoleRoundWhenStatus
Aarav Mehta Senior Full-Stack Engineer System Design Tomorrow, 2:00 PM scheduled
Sneha Kulkarni Product Designer Portfolio Deep-Dive Thu, 11:30 AM scheduled
Ananya Rao Data Scientist ML Case Study Yesterday, 4:00 PM completed · 87
Fatima Sheikh Senior Full-Stack Engineer Coding 2 days ago completed · 80
Karan Singh Product Designer Craft Interview Fri, 3:00 PM scheduled

AI-scored candidates

Every applicant is read by AI and scored for fit, skill match, and risk — so your best people surface first.

CandidateRoleStageFit ScoreSkill matchRiskRecommendation
Sneha Kulkarni
6y exp · Figma, Design Systems, User Research
Product Designer Offer 93 96% low Strong hire
Aarav Mehta
7y exp · TypeScript, React, Node.js
Senior Full-Stack Engineer Interview 91 94% low Strong hire
Ananya Rao
6y exp · Python, Machine Learning, SQL
Data Scientist Interview 88 90% low Hire
Meera Joshi
3y exp · Prospecting, CRM, Cold Outreach
Sales Development Rep Hired 86 89% low Strong hire
Priya Nair
5y exp · TypeScript, React, GraphQL
Senior Full-Stack Engineer Screening 84 88% low Hire
Fatima Sheikh
6y exp · TypeScript, Node.js, PostgreSQL
Senior Full-Stack Engineer Interview 82 85% low Hire
Karan Singh
3y exp · Figma, Prototyping, Motion Design
Product Designer Interview 79 82% medium Consider
Rahul Verma
4y exp · JavaScript, React, Node.js
Senior Full-Stack Engineer Applied 72 70% medium Consider
Arjun Reddy
1y exp · Communication, CRM
Sales Development Rep Screening 68 65% medium Consider
Vikram Iyer
2y exp · Python, Excel
Data Scientist Rejected 54 48% high Pass

💡 Notice Rahul Verma — a mid-score "hidden gem" the AI flags as high-potential despite gaps. That's the kind of call recruiters miss at volume.

Hiring analytics

Understand velocity, quality, and sourcing at a glance — no spreadsheets required.

Time to hire (days)
Trending down as AI screening removes the manual bottleneck.
38
Feb
34
Mar
31
Apr
29
May
24
Jun
21
Jul
Source of hire
Where your best candidates actually come from.
Referrals
34%
LinkedIn
27%
Careers page
21%
Job boards
18%
80/100
Average candidate quality
3
Strong-hire candidates surfaced

Business & Enterprise plans add recruiter performance, score calibration, and source-quality analytics.

Analyze a resume with AI

Upload one resume — we'll score it against a Senior Full-Stack Engineer role using the same deterministic engine the product runs. No account, no Intelligence Operations used, nothing stored.

📄
Drop a resume here, or click to choose
PDF, DOCX, or TXT · max 10 MB · one free analysis

Ask Sagar

An explainable hiring intelligence engine — not a chatbot. Ask anything about the sample candidates and pipeline; every answer is grounded in the data, with the reasoning shown.

👋 Hi, I'm Sagar. I can see the sample jobs, candidates, and interviews in this demo. Try one of the prompts below, or ask your own.

This demo copilot only sees sample data. On your account, Sagar reads your live pipeline — and never exposes candidate PII in raw form.

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