AI Case Study · HR tech
Ramped Careers
Ramped Careers: AI job-search automation
An AI-powered job-search platform that matches roles, automates applications and keeps resumes and profiles sharp across devices.
Tools
- Next.js
- FastAPI
- MongoDB
- Firebase
Time duration
16 weeks
Overview
Ramped Careers shortens the path from preference to application: AI matching, automated applications with tailored documents, and profile tools that stay in sync across devices.
Problem Statement
Job seekers burn evenings on copy-paste applications, mistargeted roles and stale resumes. Tools that only store a CV still leave matching and outreach manual. Without analytics, people cannot tell what is working, and multi-device chaos loses drafts.
Solutions
- Match roles to skills and preferences with an ML layer.
- Automate applications with customised resumes and cover letters.
- Offer resume, portfolio and LinkedIn optimisation tools.
- Surface real-time search analytics and secure multi-device profiles.
4.2×
Apps per hour
+47%
Relevant match rate
16 weeks
Delivery
Discovery insights
Survey responses gathered during discovery that ranked jobs, friction and priorities before we committed to flows.
How many applications do you submit in a typical week?
1-5
28%6-15
36%16-30
24%30+
12%
Biggest time sink in job search?
Tailoring resumes / letters
41%Finding relevant roles
29%Tracking applications
18%Interview prep
12%
Audience research
How people split across channels, screens and decision criteria. Used to weight information architecture and first-release scope.
Would you trust AI to submit an application for you?
- Yes, with review52%
- Yes, fully automated18%
- Only draft help22%
- No8%
Where do you edit your resume most often?
- Phone31%
- Laptop49%
- Both equally16%
- Tablet4%
Outcome
What the client said, and how the engagement landed after launch.
I stopped rewriting the same cover letter twenty times a week. The matches are finally close enough to trust.
Ramped Careers automates the grind between preference and application: AI matching, tailored documents and multi-device profiles.
Seekers get skill-based matches, assisted applications, resume and LinkedIn tools, and live search analytics, with human review before anything submits by default.
Stack: React/Next.js, FastAPI, MongoDB, Firebase, and an ML layer for matching and document generation.