Amor

Amor is a specialized sourcing platform designed to help companies find and hire elite software engineering talent directly from GitHub. It addresses a fundamental challenge in technical recruiting: identifying truly active, skilled developers who contribute meaningfully to open-source projects but may not be visible on traditional professional networks. The tool is built for engineering managers, in-house recruiters, talent sourcers, and recruiting agencies who need to move beyond LinkedIn to build a high-quality pipeline. Amor's core value proposition is efficiency and depth. It saves countless hours of manual searching by providing advanced filters across a massive, constantly updated dataset of over 8 million developer profiles and 66 million repositories. This allows users to pinpoint candidates based on concrete evidence of skill—like specific commit activity, project involvement, and coding consistency—rather than just self-reported resumes. By focusing on GitHub activity, Amor provides a back-to-basics look at what engineers actually build, enabling teams to hire based on demonstrated work and technical passion, leading to more informed decisions and faster placements.

Comprehensive Developer Database

Amor maintains a vast and actively monitored database of over 8 million developer profiles. This foundational feature tracks contributions across 66 million repositories, analyzing 145 billion stars to map the open-source landscape. It provides the raw data necessary to identify not just popular developers, but those with consistent, high-quality output, giving recruiters an unparalleled pool of technical talent to search from.

Advanced Filtering and Search

This feature allows for precise candidate discovery based on specific, actionable criteria. Users can filter engineers by their commit frequency, weekend coding activity, cleaned-up location data, programming languages, and contributions to specific technologies or frameworks like React or Next.js. This transforms vague sourcing goals into targeted queries, eliminating hours of manual profile screening.

Smart Profile Summaries and Insights

Amor automatically generates easy-to-skim profiles for each developer. These summaries consolidate key information, including a developer's technical interests based on starred and contributed repositories, coding activity patterns, and skill indicators. This feature provides immediate context, allowing recruiters and hiring managers to quickly assess fit without deep-diving into a full GitHub history.

Team Collaboration and Candidate Lists

Built for hiring teams, this feature enables shared workflows. Users can create, share, and manage lists of high-potential candidates. Team members can add comments and notes directly to profiles for visibility, ensuring collective knowledge is captured and streamlining the decision-making process to reduce overall time-to-hire.

For In-House Recruiters Scaling a Team

In-house recruiters at growing tech companies use Amor to build robust pipelines of pre-vetted engineering talent. By filtering for specific tech stacks, contribution consistency, and location, they can efficiently source candidates who have proven their skills through actual code, significantly reducing screening time and helping to scale engineering teams with high-quality hires.

For Recruiting Agencies Seeking an Edge

Recruiting agencies leverage Amor to access an exclusive talent pool that competitors using only LinkedIn miss. They can identify and place top-tier, "cracked" engineers who are deeply engaged in open-source work. This allows agencies to offer unique candidates to their clients, accelerating placement speed and building a reputation for sourcing exceptional technical talent.

For Engineering Managers Making Informed Hires

Engineering managers use Amor to gain deep insights into a candidate's technical passions and work ethic before the first interview. By reviewing contribution patterns and project types, they can assess culture fit and technical alignment with their team's needs, leading to more confident hiring decisions and successful long-term placements.

For Sourcing from Underrepresented Communities

Teams focused on building diverse engineering teams use Amor to tap into global and underrepresented talent pools. By searching beyond noisy location data and traditional networks, they can discover high-quality engineers based on merit and activity alone, helping to place talent from a wider range of backgrounds and geographies.

How does Amor find developer contact information?

Amor enriches profiles by automatically extracting email addresses from developers' public Git commit histories. This provides a direct, work-related contact method that is often more reliable than searching for personal emails. The platform also finds and includes links to public LinkedIn and social profiles when available.

What makes Amor different from searching on LinkedIn?

Amor focuses exclusively on GitHub, the platform where engineers showcase their actual work. While LinkedIn highlights career history and networking, Amor reveals coding frequency, project depth, and technical passions through real commit data. This allows you to find engineers who build consistently but may not actively maintain a polished LinkedIn profile.

Can I use Amor with my existing Applicant Tracking System (ATS)?

Yes, Amor is designed to integrate into your existing workflow. It offers a one-click export feature that formats candidate lists into an Ashby-compatible CSV file. This file includes enriched data like emails and tags, ready for easy import into Ashby or potentially other ATS platforms that accept CSV imports.

How accurate is the location data on Amor?

Amor uses smart data cleaning techniques to improve the accuracy of location information from GitHub profiles, which are often noisy or incomplete. It helps you search by city, region, and country by standardizing and clarifying location data, providing much more reliable geographic filtering than raw GitHub profile fields.