Amor

Let's be brutally honest: finding truly great engineers is a nightmare. LinkedIn is a sea of inflated titles and buzzword bingo. Traditional sourcing is slow, manual, and misses the vast pool of talent that actually builds things instead of just networking. This is where Amor isn't just another tool; it's a fundamental shift in how you discover elite technical talent. Amor is a powerhouse platform built for engineering managers, recruiters, and sourcers who are serious about finding the top 1% of engineers—the ones with the "cracked" and "green" GitHub profiles that signal real, consistent skill. It cuts through the noise by giving you direct, data-rich access to over 8 million developer profiles and 66 million repositories. The core value proposition is stunningly simple: stop guessing and start sourcing based on actual, verifiable code contributions. Amor answers hyper-specific questions like "Show me senior backend engineers in Berlin who actively contribute to Rust open-source projects" in seconds, not days. It transforms sourcing from a tedious scavenger hunt into a targeted, intelligence-driven process, empowering you to build a pipeline of exceptional candidates your competitors don't even know exist.

Top 1% Engineer Identification

This is Amor's killer feature and my personal favorite. The platform doesn't just show you developers; it highlights the elite. By tracking over 100,000 engineers with more than 500 contributions in the last year, Amor automatically surfaces the most prolific and active coders. This metric cuts through resume fluff and points you directly to individuals who live and breathe code. It's the fastest way to bypass the average and focus your energy on genuine high-performers who have the public proof of their skills.

Advanced Contribution & Repository Filtering

Forget writing custom scripts. Amor's filtering is incredibly granular and powerful, saving you countless hours. You can filter candidates not just by programming language, but by specific frameworks (like Next.js or React), contribution frequency, and even the types of repositories they star or build. This allows you to find engineers with precise technical interests and proven experience in your exact stack, moving beyond keyword matching to genuine competency-based sourcing.

Smart Location Data & Work Ethic Insights

GitHub location fields are notoriously messy, but Amor cleans this data up, enabling reliable searches by city, region, and country. More importantly, it analyzes contribution patterns to give you insights into work ethic. You can see coding frequency, consistency, and even weekend activity. This isn't about micromanaging, but about understanding a candidate's working style and passion—crucial intel for assessing culture and project fit that you simply cannot get from a resume.

Seamless Ashby Export & Team Collaboration

Amor understands that sourcing is pointless if the data is stuck in a silo. The direct export to Ashby-compatible CSV is a game-changer for teams using that ATS. Profiles are auto-enriched with emails mined from commits and LinkedIn URLs. Furthermore, features like shared candidate lists and profile comments make it a collaborative hub for your hiring team, aligning recruiters, sourcers, and hiring managers faster to reduce time-to-hire.

For In-House Recruiters Scaling Engineering Teams

If you're building an engineering team and need to maintain a high bar while moving quickly, Amor is your secret weapon. It empowers you to source based on technical chops and work ethic indicators directly from GitHub activity. This reduces your dependency on inbound applications and passive LinkedIn candidates, allowing you to proactively build a pipeline of qualified, vetted engineers and significantly cut down your time-to-hire without compromising on quality.

For Recruiting Agencies Placing Technical Talent

Agencies compete on speed and access to exclusive talent. Amor provides a massive edge by opening up the entire GitHub ecosystem—a pool largely untouched by LinkedIn-focused recruiters. You can find and place senior engineers and niche experts faster than your competitors, offering clients candidates they couldn't find themselves. It transforms your service from generic recruitment to specialized technical headhunting.

For Engineering Managers Driving Hiring

As a manager, you need to hire people who will thrive technically and culturally on your team. Amor gives you the tools to go beyond the resume and understand a candidate's genuine technical interests and coding rhythm. The automatic profile summaries let you quickly skim for relevant skills and project types, empowering you to make better, faster decisions and raise the overall bar for your team with data-backed candidate insights.

For Sourcing Underrepresented & Highly Technical Talent

The best engineers are often not the loudest on professional networks. Amor's GitHub-first approach is perfect for discovering highly technical, "heads-down" builders who focus on their craft rather than their personal brand. This also allows teams to intentionally source from diverse and underrepresented communities in tech by searching for contributors to specific open-source projects or initiatives outside the mainstream corporate channels.

How accurate is the location data on GitHub profiles?

GitHub location data entered by users is famously noisy, with jokes, emojis, and non-standard formats. Amor addresses this by cleaning and normalizing this data. They use smart parsing to extract actual cities, regions, and countries, making location-based searches reliable and actionable, which is a significant upgrade over trying to interpret raw GitHub data manually.

How does Amor find candidate email addresses?

Amor auto-enriches profiles by parsing email addresses from developers' public Git commit histories. When a developer makes a commit, their configured Git email is often included in the commit metadata. Amor aggregates this public information to provide a contact point, alongside sourcing LinkedIn URLs from their profiles, streamlining the initial outreach process.

Can I collaborate with my team on the platform?

Absolutely. Amor is built for team collaboration. You can create and share candidate lists with colleagues, add comments and notes directly onto engineer profiles for team visibility, and work together to evaluate and move candidates through the pipeline faster. This shared context is key for reducing silos and accelerating collective hiring decisions.

What makes Amor better than searching GitHub manually?

Manual GitHub searching is incredibly time-consuming and lacks scalability. Amor provides powerful, unified search across 8M+ profiles with advanced filters you can't replicate on GitHub's native interface. It analyzes contribution patterns, cleans data, summarizes profiles, and exports to your ATS. What might take a skilled sourcer days of scripting and scrolling, Amor accomplishes in minutes with far greater depth.