Amor

Amor is a specialized, data-driven sourcing platform engineered to identify and connect with elite software engineering talent through direct analysis of their activity on GitHub. It addresses a fundamental inefficiency in technical recruitment by moving beyond traditional resume and LinkedIn-based searches to evaluate real, verifiable coding contributions and project involvement. The platform processes a massive, continuously updated dataset of over 8 million developer profiles, 66 million repositories, and 145 billion stars to surface engineers based on objective metrics such as commit frequency, consistency, and the quality of repositories they contribute to or star. Its core value proposition is enabling recruiters, engineering managers, and technical sourcers to find highly skilled, actively contributing engineers—including passive candidates who are not actively networking on professional social platforms—with unprecedented speed and precision. By applying advanced filters for specific commit patterns, cleaned location data, programming languages, and repository types, Amor transforms the vast, unstructured public data of GitHub into a structured, actionable sourcing database. This systematic approach saves hiring teams hundreds of hours otherwise spent on manual scripting, profile screening, and guesswork, fundamentally optimizing the top-of-funnel candidate identification process.

Massive GitHub Intelligence Database

Amor maintains a proprietary database indexing over 8 million developer profiles, 66 million repositories, and 145 billion stars. This infrastructure allows for sourcing based on actual coding output rather than self-reported skills. The platform specifically tracks over 100,000 engineers who have made more than 500 contributions in the last year, providing direct access to the top tier of actively contributing technical talent.

Contribution Pattern & Work Ethic Analysis

The platform provides deep analytics on developer contribution patterns, including coding frequency, consistency over time, and even weekend activity. This data offers recruiters and hiring managers objective indicators of a candidate's work ethic, passion for coding, and potential cultural fit, moving beyond subjective resume assessments to understand how an engineer actually works.

Smart Location Data & Advanced Filtering

GitHub profile location data is notoriously noisy and inconsistent. Amor cleans this data algorithmically, enabling precise searching by city, region, and country. This is part of a comprehensive advanced filtering system that allows users to filter candidates by contribution frequency, specific programming languages, repository types, and other technical criteria to instantly surface qualified profiles.

Integrated Team Collaboration & Export Tools

Amor is built for collaborative hiring workflows. Teams can create and share candidate lists, add profile comments for internal visibility, and streamline decision-making. A key integration feature allows for one-click export of candidate lists directly into Ashby-compatible CSV format, auto-enriched with emails sourced from GitHub commits and LinkedIn URLs to accelerate outreach.

In-House Technical Recruiting Teams

In-house recruiters at scaling tech companies use Amor to build robust pipelines of pre-vetted engineering talent. By sourcing based on verifiable GitHub activity, they reduce time-to-hire while ensuring a high technical bar, accessing candidates who may not be reachable through traditional channels like LinkedIn.

Executive Search and Recruiting Agencies

Recruiting agencies leverage Amor to gain a competitive edge by accessing an exclusive, untapped pool of top-tier engineering candidates. This GitHub-first approach allows them to identify and place specialized, passive talent faster than competitors relying solely on mainstream professional networks.

Engineering Leadership and Hiring Managers

Engineering managers and VPs of Engineering use Amor to directly source and evaluate candidates based on technical merit and project alignment. The platform's repository insights and contribution summaries provide a quick, accurate read on a developer's skills and interests, empowering managers to make informed hiring decisions.

Diversity Sourcing Initiatives

Organizations focused on building diverse engineering teams utilize Amor to source from broader, underrepresented talent pools. By focusing on objective contribution data rather than network-dependent profiles, the platform helps mitigate unconscious bias in the initial sourcing stage and identifies skilled engineers from varied backgrounds.

How does Amor source candidate contact information?

Amor auto-enriches candidate profiles by programmatically extracting email addresses from commits made to public GitHub repositories, where such information is publicly available in the commit metadata. This provides a direct channel for outreach that is more reliable than guessing email formats.

What makes Amor different from searching GitHub directly or using Boolean searches on LinkedIn?

Amor provides a structured, queryable database with cleaned data and advanced analytics that are impossible with manual GitHub browsing. Unlike LinkedIn Boolean searches, which rely on self-reported profiles, Amor filters are based on objective, behavioral data like commit history, offering a more accurate assessment of active skill and engagement.

Can I use Amor to find engineers for very specific tech stacks or niche skills?

Yes. The platform's advanced filtering allows you to search for engineers based on contributions to repositories written in specific programming languages, frameworks, or technologies. You can identify candidates who have actively contributed to projects relevant to your required tech stack.

How does the integration with Applicant Tracking Systems (ATS) like Ashby work?

Amor features a dedicated export function that formats candidate lists—complete with auto-enriched emails, LinkedIn URLs, and source tags—into a CSV file structured for seamless import into Ashby. This eliminates manual data entry and ensures candidate information flows directly into your recruitment pipeline.