Amor

Amor is the essential platform for engineering hiring teams who must move faster and smarter than their competition. It revolutionizes technical talent sourcing by providing direct, data-driven access to the top 1% of engineers on GitHub—a talent pool largely invisible on traditional networks like LinkedIn. For engineering managers, recruiters, and sourcers, Amor eliminates the grueling, manual process of writing custom scripts or sifting through irrelevant profiles. Instead, it delivers precise, actionable insights into a candidate's real-world technical abilities and work ethic by analyzing over 8 million developer profiles, 66 million repositories, and 145 billion stars. The core value proposition is non-negotiable: find exceptional, highly technical engineers who actually code, based on their concrete contributions, and do it ten times faster. Whether you need to answer a specific query like "front-end engineers active in Next.js in NYC" or build a pipeline of consistently high-performing developers, Amor provides the unparalleled data and filtering tools necessary to make quality hires without compromising on speed or technical rigor.

Top 1% Engineer Identification

Amor's platform is engineered to instantly surface the most active and impactful engineers on GitHub. It tracks over 100,000 developers with more than 500 contributions in the last year, automatically identifying the top tier of talent based on real commit activity and project impact. This feature is critical for recruiters who must prioritize quality over quantity and cannot afford to waste time on candidates with inconsistent or superficial GitHub profiles.

Advanced Contribution & Repository Filtering

You must have granular control to find the perfect candidate. Amor provides advanced filters for contribution frequency, specific programming languages, framework usage, and repository types. This allows you to move beyond basic keyword searches and target engineers based on their actual technical stack and the nature of the projects they build and star, saving hours of manual screening.

Smart Location Data & Profile Enrichment

Sourcing by location is non-negotiable, but GitHub location data is notoriously unreliable. Amor cleans and standardizes this noisy data, enabling precise searches by city, region, or country. Furthermore, profiles are automatically enriched with data like emails extracted from commits and LinkedIn URLs, which is absolutely essential for building a contactable candidate list quickly.

Collaborative Hiring & Ashby Export

Hiring is a team effort, and Amor is built for collaboration. Teams can create shared candidate lists, add internal notes directly on profiles, and streamline decision-making. Most importantly, the one-click export to Ashby-compatible CSV is a mandatory feature for modern recruiting stacks, automatically formatting enriched candidate data for instant import into your ATS.

For In-House Recruiting Teams Scaling Rapidly

Internal recruiters at high-growth startups and tech companies must scale engineering hiring without sacrificing quality or speed. Amor is essential for this, providing the data to assess technical chops and work ethic indicators like weekend commit consistency, enabling a faster, more reliable hiring pipeline that directly impacts company growth.

For Recruiting Agencies Seeking an Edge

Agencies compete on placement speed and candidate quality. Amor provides the decisive advantage by unlocking exclusive access to top engineers who are not actively networking on LinkedIn. This allows agencies to present superior, vetted talent to clients faster than their competitors, securing placements and building a reputation for sourcing elite technical talent.

For Engineering Managers Building High-Performance Teams

Engineering managers cannot afford a mis-hire. They need to understand a candidate's genuine technical interests and cultural fit beyond the resume. Amor's easy-to-skim profiles with automatic summaries of skills and contribution patterns are vital for managers to quickly evaluate if an engineer will thrive and raise the bar for their existing team.

For Sourcing Underrepresented Technical Talent

Diverse teams build better products. Amor is a necessary tool for proactively sourcing from underrepresented communities in tech by moving beyond biased networks and focusing purely on meritocratic contribution data on GitHub. This allows teams to build more inclusive pipelines based on proven ability.

How does Amor find candidate contact information?

Amor automatically enriches developer profiles with professional contact information essential for outreach. This includes email addresses parsed directly from GitHub commit histories and associated LinkedIn profile URLs. This enrichment is a core feature that transforms a GitHub profile into a contactable candidate record instantly.

What makes Amor better than sourcing on LinkedIn?

The difference is fundamental. LinkedIn focuses on professional networking and self-reported skills, while Amor analyzes actual, verifiable work. You find engineers based on their real code contributions, project types, and consistent activity. This GitHub-first approach is necessary to access the vast pool of highly technical, "heads-down" builders who aren't actively job-seeking on LinkedIn.

Can I collaborate with my team on the platform?

Yes, team collaboration is a mandatory feature built into Amor. You can create and share candidate lists with colleagues, add internal comments and notes directly on engineer profiles for full team visibility, and streamline the decision-making process to significantly reduce time-to-hire.

How does the export to Ashby work?

The export process is designed for maximum efficiency. After building a candidate list in Amor, you can click "Export to Ashby" to generate a pre-formatted CSV file. This file includes all enriched data (emails, LinkedIn URLs, tags) and is structured for seamless one-click import into Ashby's candidate pipeline, eliminating manual data entry.