CV Matchr

Built an AI-powered CV screening tool that matches candidates to job openings using natural language processing. The system scores resumes against job descriptions and provides candidates with specific feedback on how to improve their applications. Integrated real-time analysis to help both recruiters filter applicants and job seekers optimize their CVs for better match rates.

AI

AI

Recruitment

Recruitment

SaaS

SaaS

Overview

We built an AI platform that matches CVs to job opportunities and scores applications in real time. The system analyzes candidate profiles against job requirements, then provides specific feedback on how to improve match rates. CV Matchr helps job seekers understand exactly what recruiters are looking for and how to position themselves accordingly.

Team

Deliverables

AI-powered matching engine that analyzes CVs against job descriptions to identify best-fit candidates

CV parsing engine with real-time scoring and optimization features

Web application for job candidates to upload resumes and discover matching opportunities. Built with React frontend and Python backend for resume parsing and matching algorithms.

Integration tools for employers to post jobs, review matches, and manage candidate pipelines. Built employer dashboards with real-time application tracking and automated screening workflows.

We built a complete data pipeline that processes resumes and job descriptions through multiple stages. Raw documents flow through our extraction system, get cleaned and standardized, then feed into our ML training pipeline. The setup includes automated data validation, feature engineering for text matching, and model versioning to track performance improvements over iterations.

We launched CV Matchr's MVP with all core features working end-to-end. The platform could accept job postings, parse CVs, run AI-powered matching, and deliver scored results through a clean interface. Early user testing validated the matching accuracy and UI flow. The MVP gave the client a working product to demo to potential customers and gather real feedback for the next iteration.

Working with Axel and Dev, In transformed our concept into a functioning product. Their practical approach meant we got exactly what we needed—a working application, not just promises. They delivered clean code, provided solid technical guidance throughout the build, and helped us make smart decisions about our tech stack. We'd recommend them to anyone who needs to ship quality software.

Marie Nord

01

CV Matchr uses AI to match candidates with job openings at scale. We built this internal tool to help our recruiting partners screen thousands of applications efficiently. The system parses both CVs and job descriptions, then uses semantic matching to rank candidates by relevance. Instead of keyword matching, it understands context — recognizing that "React developer" and "frontend engineer with React experience" mean the same thing. We integrated OpenAI's API for the matching logic and built a Next.js dashboard for recruiters to review results. The tool processes PDFs, Word docs, and plain text, extracting structured data from unstructured resumes. This cut initial screening time from hours to minutes for high-volume recruiting campaigns. Recruiters get ranked candidate lists with match scores and highlighted relevant experience, letting them focus on the most promising applicants first.

Job seekers need to know if their CV matches what employers want. Employers need efficient ways to screen thousands of applications. CV Matchr addresses both sides of this problem with AI-powered matching and feedback tools. We built an AI system that analyzes CVs against job descriptions, providing candidates with specific improvement suggestions while helping employers identify the most relevant applicants faster. The platform uses natural language processing to understand both technical requirements and soft skills, moving beyond simple keyword matching to semantic understanding.

01

CV Matchr uses AI to match candidates with job openings at scale. We built this internal tool to help our recruiting partners screen thousands of applications efficiently. The system parses both CVs and job descriptions, then uses semantic matching to rank candidates by relevance. Instead of keyword matching, it understands context — recognizing that "React developer" and "frontend engineer with React experience" mean the same thing. We integrated OpenAI's API for the matching logic and built a Next.js dashboard for recruiters to review results. The tool processes PDFs, Word docs, and plain text, extracting structured data from unstructured resumes. This cut initial screening time from hours to minutes for high-volume recruiting campaigns. Recruiters get ranked candidate lists with match scores and highlighted relevant experience, letting them focus on the most promising applicants first.

Job seekers need to know if their CV matches what employers want. Employers need efficient ways to screen thousands of applications. CV Matchr addresses both sides of this problem with AI-powered matching and feedback tools. We built an AI system that analyzes CVs against job descriptions, providing candidates with specific improvement suggestions while helping employers identify the most relevant applicants faster. The platform uses natural language processing to understand both technical requirements and soft skills, moving beyond simple keyword matching to semantic understanding.

02

AI-powered candidate screening system

We built the MVP that launched CV Matchr: a job-matching platform with AI-powered CV analysis. The system scores uploaded resumes, provides specific improvement suggestions, and matches candidates to relevant positions based on their skills and experience. For employers, we created tools to automate candidate screening and ranking — reducing time-to-shortlist while improving match quality. The dual-sided marketplace connected job seekers with better opportunities and gave recruiters more qualified candidates faster.

02

AI-powered candidate screening system

We built the MVP that launched CV Matchr: a job-matching platform with AI-powered CV analysis. The system scores uploaded resumes, provides specific improvement suggestions, and matches candidates to relevant positions based on their skills and experience. For employers, we created tools to automate candidate screening and ranking — reducing time-to-shortlist while improving match quality. The dual-sided marketplace connected job seekers with better opportunities and gave recruiters more qualified candidates faster.

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FAQ

Get quick answers about working with us and our approach to digital solutions.

What’s included in a monthly retainer?

01

Each retainer includes a set number of design or strategy requests per month, priority turnaround, and a dedicated point of contact. It’s built for teams who want ongoing support without starting from scratch every time.

How many requests can I make per month?

02

We typically handle up to two active requests at a time, with new ones queued as they’re completed. Most deliverables are turned around within 48–72 hours, depending on complexity.

Is a retainer better than a one-off project?

03

If you need ongoing design support, faster turnarounds, or regular iterations, a retainer is often more cost-effective and collaborative than starting fresh each time.

Who will I be working with?

04

You’ll work directly with senior designers and strategists. No middle layers, no fluff—just experienced people doing the work.

Do you work with international clients?

05

Yes. Most of our clients are remote. We’re fully set up to collaborate across time zones with clear communication and shared tools.

Let's talk shop

Karl Johans gate 25. Oslo Norway

Let's talk shop

Karl Johans gate 25. Oslo Norway

Let's talk shop

Karl Johans gate 25. Oslo Norway