Amor

Amor is an innovative sourcing platform specifically designed to aid engineering managers, recruiters, and sourcers in identifying top-tier software engineering talent directly from GitHub activity. Unlike traditional recruitment tools, Amor addresses the challenge of locating highly skilled engineers who may not maintain an active presence on conventional professional networks like LinkedIn. By harnessing data from over 8 million developer profiles, 66 million repositories, and 145 billion stars, Amor provides actionable insights into a candidate's coding contributions, work ethic, and technical interests. This platform excels in efficiency and quality, significantly reducing the time spent on manual searches by enabling precise queries based on commit activity, project contributions, and cleaned location data. With Amor, recruiters can swiftly answer specific queries, such as "which front-end engineers committed to Next.js repos and live in NYC?" allowing teams to engage with the top 1% of engineers who consistently contribute to their fields. By focusing on GitHub-first sourcing, Amor helps organizations discover exceptional talent faster than their competitors.

Advanced Candidate Search

Amor's advanced search capabilities allow users to filter candidates based on detailed criteria such as commit activity, project contributions, and coding patterns. This precision helps identify the most suitable engineers quickly.

Contribution Patterns Analysis

This feature enables recruiters to analyze candidates' coding frequency, consistency, and even weekend activity, providing insights into their work ethic and suitability for specific roles within a team.

Smart Location Data

Amor cleans up the often noisy location data found in GitHub profiles, enabling users to search candidates by city, region, or country. This ensures that recruiters can find local talent efficiently and effectively.

Easy Profile Summaries

The platform offers automatic summaries of each developer's interests, skills, and activity. This feature allows recruiters to skim through profiles quickly, saving valuable time in the candidate evaluation process.

Streamlined Sourcing for In-House Recruiters

In-house recruiters can leverage Amor to scale their engineering hiring processes effectively. By obtaining insights into candidates' technical skills and work ethics, they can reduce the time-to-hire while maintaining quality.

Rapid Placement for Recruiting Agencies

Recruiting agencies can use Amor to place engineers faster than competitors who rely solely on LinkedIn. The platform gives access to exclusive candidates, enhancing the agency's ability to fill positions quickly.

Enhanced Team Fit for Engineering Managers

Engineering managers can utilize Amor to find candidates who not only possess the necessary skills but also fit well within their team culture. This helps in building cohesive and productive teams.

Collaborative Hiring Processes

Amor facilitates collaboration among hiring teams by allowing them to create and share candidate lists, add comments, and share profiles directly with hiring managers. This collective approach streamlines decision-making and reduces hiring times.

How does Amor source candidates?

Amor sources candidates by analyzing GitHub activity, including developer profiles, project contributions, and coding patterns. This approach uncovers highly skilled engineers who may not be visible on traditional platforms.

Can I filter candidates by specific programming languages?

Yes, Amor allows users to filter candidates based on the programming languages they use, along with other criteria such as contribution frequency and location. This ensures you find candidates with the exact technical skills you need.

How does the platform enrich candidate profiles?

Amor enriches candidate profiles by automatically including emails from GitHub commits, LinkedIn URLs, and smart tags. This additional information aids in better organization and outreach efforts.

Is there a limit to the number of profiles I can view?

Amor offers a free trial with limited search results, allowing users to test the platform. For extensive searches and candidate evaluations, users can choose from paid plans that suit their team size and needs.