LAPRAS is a career-matching platform that utilizes AI to automatically generate profiles and score engineers' technical skills based on their online outputs, such as GitHub contributions and technical articles. This enables companies to directly scout qualified candidates, addressing the challenge of efficiently connecting skilled engineers with job opportunities.
Funding
$9.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Recruiting skilled engineers is challenging due to the difficulty in accurately assessing technical abilities and matching them with suitable job opportunities. Traditional methods rely heavily on self-reported skills and manual resume screening, which can be inefficient and subjective. Companies struggle to identify candidates who possess the specific expertise and experience required for their open positions.
Solution
LAPRAS is an AI-powered career-matching platform that automates the creation of engineer profiles and evaluates their technical skills based on online contributions. The platform analyzes publicly available data, such as GitHub repositories, technical blog posts, and conference presentations, to generate a comprehensive skill profile and LAPRAS Score. This score reflects an engineer's technical capabilities and influence within the developer community. Companies can then use these AI-driven insights to directly scout and connect with qualified candidates, streamlining the recruitment process and improving the quality of hires.
Target Audience
The primary users are software engineers looking for job opportunities and companies seeking to hire skilled technical talent, including startups and large enterprises.
Features
- Automated profile generation using AI analysis of online technical activities
- LAPRAS Score: a quantitative assessment of technical skills and influence based on public contributions
- AI-powered review of technical articles to evaluate content quality and provide feedback
- Skill tagging: identification of key skills and areas of expertise based on activity analysis
- Activity log: visualization of an engineer's contributions, including code commits, blog posts, and event participation
- Direct scouting: enables companies to directly contact engineers based on their skills and experience
- Analytics dashboard: provides insights into profile views and company interest