Amor

Amor is a revolutionary sourcing platform built for the modern, technical hiring team. It moves beyond the curated world of LinkedIn to find exceptional software engineers where they truly showcase their skills: on GitHub. By analyzing the raw data of what developers actually build and contribute to, Amor provides an authentic, code-first view of talent. The platform taps into a massive dataset of over 8 million developer profiles, 66 million repositories, and 145 billion stars to help engineering managers, recruiters, and sourcers discover highly technical, often under-the-radar candidates. Its core mission is to save you countless hours of manual work by replacing custom scripts and endless browsing with intelligent, filterable searches. You can answer precise, complex questions in seconds, like finding front-end engineers in a specific city who regularly commit to Next.js projects. Amor helps you identify the top 1% of engineers based on real contribution patterns, clean location data, and project insights, giving you access to a pool of candidates who are more focused on coding than networking. With features like one-click export to Ashby-compatible CSV, Amor streamlines the entire process from discovery to outreach, enabling teams to hire better engineers faster and gain a competitive edge in the talent market.

Vast GitHub Intelligence Engine

Amor's power comes from its deep analysis of the entire GitHub ecosystem. The platform continuously tracks and analyzes over 8 million developer profiles and 66 million repositories, processing a staggering 145 billion stars. This isn't just surface-level data; Amor digs into actual commit history, contribution frequency, and repository activity to build a comprehensive, authentic picture of a developer's skills, interests, and work ethic, far beyond what a resume or social profile can show.

Advanced, Precise Filtering

Stop wasting time on manual screening. Amor's advanced filtering allows you to pinpoint candidates with surgical precision. You can filter by programming languages, specific frameworks (like React or Next.js), contribution frequency, consistency, and even weekend coding activity. Combined with smart, cleaned-up location data that interprets noisy GitHub location fields, you can find engineers in a specific city or region who match your exact technical stack and demonstrated work patterns in seconds.

Easy-to-Skim Candidate Profiles

Amor transforms complex GitHub activity into clear, actionable insights. Each developer profile features an automatic summary of their technical interests, top skills, and recent activity. You can quickly understand the types of projects they build, the repositories they star, and their coding habits without having to manually parse hundreds of commit messages. This allows you to spend less time on each profile while making more informed assessments.

Seamless Team Collaboration & Export

Built for teams that need to move fast, Amor turns sourcing into a collaborative process. You can create and share candidate lists with your team, add internal notes and comments directly on profiles for visibility, and streamline decision-making. Most importantly, you can export your curated lists directly to your ATS. With one-click export to Ashby-compatible CSV, profiles are auto-enriched with emails from commits and LinkedIn URLs, making the transition from discovery to outreach effortless.

For In-House Recruiting Teams

Scale your engineering hiring efficiently without compromising on quality. In-house recruiters can use Amor to find expert engineers with proven technical chops and strong work ethic indicators directly from their code. By accessing a pool of candidates who may not be active on traditional job boards, you can reduce time-to-hire, build a stronger pipeline, and make data-backed arguments for culture and skill fit to your hiring managers.

For Technical Recruiting Agencies

Gain a significant competitive advantage by sourcing where others aren't looking. Recruiting agencies can use Amor to access exclusive, high-quality candidates that LinkedIn-only competitors don't know exist. This allows you to place top senior engineering talent faster, demonstrate deep market knowledge to clients, and build a reputation for finding exceptional, "cracked" engineers with consistently green GitHub profiles.

For Engineering Managers

Hire engineers who will truly thrive on your team. Engineering managers can use Amor to go beyond the interview and understand a candidate's genuine technical passions and coding consistency. By reviewing contribution patterns and project summaries, you can assess real-world skills and work ethic, helping you raise the bar for your team and make faster, more confident hiring decisions that are rooted in tangible evidence.

For Building Diverse Talent Pools

Proactively source from underrepresented and untapped talent communities. Because Amor discovers talent based on actual code contributions rather than network size or self-promotion, it helps you find highly skilled engineers from diverse backgrounds who may be overlooked by traditional sourcing methods. This enables you to build a more inclusive and technically excellent pipeline.

How does Amor find candidate contact information?

Amor intelligently enriches profiles by parsing email addresses from developers' public Git commit history. This is a common and reliable source for professional contact details within the developer community. The platform also finds and includes LinkedIn and other social profile URLs when available, providing multiple channels for outreach directly from the exported candidate lists.

What makes Amor better than searching on LinkedIn or GitHub directly?

Amor saves you hours of manual work by applying powerful intelligence to the GitHub data you'd otherwise have to sift through manually. Instead of writing custom scripts or browsing endlessly, Amor's filters let you ask precise questions instantly. It also cleans noisy location data, summarizes complex activity into skimmable profiles, and facilitates team collaboration—functionality that simply doesn't exist on the native platforms.

How accurate is the location data?

GitHub location fields are famously inconsistent (e.g., "Earth," "The Cloud"). Amor uses smart data cleaning techniques to interpret, standardize, and geo-locate these entries. This allows you to search reliably by city, region, or country, turning an otherwise useless field into a powerful, filterable criterion for local or remote hiring strategies.

Can I try Amor before committing to a plan?

Yes! Amor offers a free tier that allows you to experience the platform with limited search results. This lets you test the advanced filters, explore profiles, and understand the workflow without requiring a credit card. You can upgrade to a paid plan at any time to unlock full access and higher search limits.