Amor

Amor is an enterprise-grade recruitment intelligence platform engineered to transform how organizations identify and hire elite software engineering talent. It directly addresses the critical bottleneck of technical sourcing by providing data-driven, actionable insights into the global developer community, moving beyond traditional networking platforms like LinkedIn. The platform leverages GitHub's vast ecosystem, continuously analyzing over 8 million developer profiles, 66 million repositories, and 145 billion stars to surface candidates based on genuine technical activity and contribution patterns. Designed for engineering managers, in-house recruiters, sourcers, and recruiting agencies, Amor empowers teams to answer complex, high-signal sourcing questions in seconds—such as finding front-end engineers actively contributing to specific frameworks in a target city. By automating the manual, time-intensive process of writing custom scripts or sifting through noisy profile data, Amor significantly reduces time-to-hire, improves candidate quality, and provides a competitive edge in securing top-tier, often "hidden" talent who prioritize building over networking. The platform's core value proposition is delivering a measurable ROI through increased sourcing efficiency, access to an untapped talent pool, and data-backed insights into a candidate's technical expertise and work ethic.

Intelligent GitHub Talent Graph

Amor maintains a dynamic, constantly updated database of over 8 million developer profiles, mapping contributions, stars, and repository activity. This feature allows for granular filtering across millions of data points, enabling recruiters to find engineers based on specific commit history, project types, and technical interests, transforming raw GitHub data into a searchable talent marketplace with unparalleled depth and accuracy for technical recruiting.

Contribution Pattern & Work Ethic Analytics

The platform provides deep analytics on developer activity, including coding frequency, consistency, and even weekend contributions. This goes beyond a simple "green squares" view, offering quantifiable metrics to assess a candidate's engagement, passion, and potential cultural fit. Teams can evaluate work ethic indicators to identify engineers who are not just skilled but are consistently active and dedicated builders.

Smart Location Data & Advanced Filtering

Amor cleans and standardizes the notoriously noisy location data found on GitHub profiles, enabling precise searches by city, region, or country. Combined with advanced filters for programming languages, contribution volume, and repository topics, this feature allows for hyper-targeted sourcing campaigns, saving hours of manual screening and enabling the rapid assembly of qualified candidate lists for specific roles and locations.

Seamless Ashby Integration & Team Collaboration

Amor streamlines the workflow from discovery to applicant tracking with a one-click export to Ashby-compatible CSV, auto-enriched with emails from commits and LinkedIn URLs. Furthermore, built-in collaboration tools like shared candidate lists and profile comments enable hiring teams to align quickly, share insights, and accelerate collective decision-making, reducing friction and time-to-hire.

Scaling High-Growth Startup Engineering Teams

In-house recruiting teams at fast-scaling startups use Amor to systematically build a pipeline of high-caliber engineers who match specific tech stacks and cultural indicators. By identifying "cracked engineers with green GitHubs" who are actively contributing, they can hire exceptional talent faster than competitors relying on conventional methods, directly impacting product velocity and growth.

Recruiting Agencies Securing Exclusive Placements

Technical recruiting agencies leverage Amor to access a candidate pool invisible to LinkedIn-centric competitors. By sourcing from underrepresented communities and finding highly technical engineers based on proven work, agencies can place top-tier senior talent faster, securing exclusive placements and building a reputation for accessing premium, off-market candidates.

Engineering Managers Raising the Technical Bar

Engineering managers utilize Amor to gain instant summaries of a candidate's technical interests and contribution history. This allows for informed, efficient screening, ensuring candidates not only have the required skills but also demonstrate a genuine passion for relevant technologies and a consistent work ethic, leading to higher-quality hires that thrive on the team.

Building Diverse and Specialized Talent Pipelines

Talent acquisition leaders employ Amor's advanced filtering to proactively build pipelines for niche or high-demand roles, such as experts in a specific framework or language. The ability to search by repository topics and contribution patterns enables targeted outreach to diverse, highly skilled engineers who may not be actively job-seeking, enriching overall talent strategy.

How does Amor source its candidate data?

Amor aggregates and analyzes public data from the GitHub platform, including developer profiles, repository contributions, stars, and commit histories. The system tracks over 8 million profiles and processes this information to provide clean, searchable, and insightful metrics on coding activity, technical interests, and geographical location, all in compliance with GitHub's terms of service.

Can I export candidate data to my Applicant Tracking System (ATS)?

Yes, Amor features a dedicated export function designed for seamless integration with Ashby. Candidate lists can be exported with one click into an Ashby-compatible CSV format. This file is automatically enriched with available email addresses sourced from commit histories and includes LinkedIn URLs and relevant tags for easy import and organization within your ATS.

How does Amor ensure candidate quality and relevance?

Amor ensures quality through data-driven signals rather than self-reported skills. The platform highlights engineers in the top 1% by contribution volume and analyzes the consistency and nature of their work. Features like repository insights and contribution pattern analytics provide a substantive view of a developer's actual expertise and work ethic, far surpassing the signal from a traditional resume or social profile.

Is Amor suitable for hiring non-engineering roles?

No, Amor is specifically engineered for sourcing software engineering and technical development talent. Its core functionality is built around analyzing GitHub activity, code contributions, and technical repository data. It is not designed for sourcing candidates in marketing, sales, operations, or other non-technical disciplines where GitHub activity is not a relevant professional signal.