LinkedIn has over 1 billion users, and somehow recruiters still can't find qualified candidates. The problem isn't the size of the talent pool—it's that most of that pool is invisible, passive, or poorly indexed by LinkedIn's search.

Arya by Leoforce uses advanced machine learning with access to a vast talent pool of over 850 million profiles across LinkedIn, GitHub, Stack Overflow, AngelList, and other platforms. It's AI-powered candidate sourcing that finds people you wouldn't find manually, ranks them by fit, and reaches out automatically.

This is either the future of sourcing or a way to spam 850 million people with poorly targeted InMails. Let's figure out which.

What Arya Actually Does

Arya is an AI sourcing platform that automates candidate discovery, matching, and outreach. Here's the workflow:

1. Multi-Platform Sourcing: Arya searches across 850+ million profiles on LinkedIn, GitHub, Stack Overflow, AngelList, job boards, and public databases. It aggregates data from multiple sources to build comprehensive candidate profiles.

2. Machine Learning Matching: You input job requirements. Arya's AI analyzes those requirements and matches candidates based on skills, experience, job history, education, and inferred career trajectory. The algorithm learns from your feedback—when you mark candidates as good or bad fits, it refines future recommendations.

3. Automated Ranking: Candidates are ranked by predicted fit using machine learning models trained on historical hiring data. Top-ranked candidates bubble to the top of your pipeline automatically.

4. Automated Outreach: Arya can send personalized outreach messages to candidates via email, LinkedIn, or other channels. Templates are customizable, and the system tracks responses and engagement.

5. Pipeline Management: Track candidate engagement, responses, and progression through your pipeline in Arya's dashboard. Integrates with major ATS platforms for seamless handoff.

The promise: find passive candidates you'd never discover manually, rank them intelligently, and automate first-touch outreach. Essentially, AI-powered sourcing at scale.

What This Gets Right

Access to passive candidates. LinkedIn Recruiter shows you active job seekers and people with "Open to Work" flags. Arya finds people who aren't actively looking but match your criteria. That's valuable in competitive talent markets.

Multi-platform aggregation is genuinely useful. A developer's GitHub shows work quality better than their LinkedIn. A designer's Dribbble portfolio matters more than their resume. Arya pulls data from multiple sources to build richer candidate profiles.

Machine learning improves over time. The more you use Arya and provide feedback, the better it gets at finding candidates you'll actually want. This isn't static keyword matching—it's adaptive learning.

Saves sourcing time. Manual sourcing takes 10-15 hours per role for skilled recruiters. Arya can surface candidates in minutes. For high-volume recruiting, that time savings is massive.

Diversity sourcing features. Arya includes tools to surface diverse candidate pools and reduce bias in sourcing. You can set diversity goals and track pipeline demographics.

What This Gets Wrong (Or Raises Red Flags)

850 million profiles sounds great until you realize most are garbage. Volume doesn't equal quality. Aggregating data from every possible source means tons of outdated profiles, duplicates, and irrelevant matches.

Automated outreach can easily become spam. When you make it this easy to contact hundreds of candidates, the temptation is to blast generic messages at everyone. That's how you destroy your employer brand and get blacklisted.

AI matching still requires good input. If your job requirements are vague or wrong, Arya will confidently surface terrible candidates. Garbage in, garbage out—machine learning doesn't fix bad role definitions.

Candidates might not appreciate being "found." Passive candidates who aren't on LinkedIn with "Open to Work" flags often don't want recruiting outreach. AI-sourced outreach can feel invasive if not done carefully.

Platform access and scraping concerns. Aggregating 850M profiles from LinkedIn, GitHub, etc., raises questions about data sourcing and compliance. Is this data obtained ethically and legally? Terms of service violations are a real risk.

When Arya Makes Sense

Hard-to-fill specialized roles. When you need niche skills and LinkedIn Recruiter isn't surfacing qualified candidates, Arya's multi-platform sourcing can find people others miss.

High-volume recruiting teams. If you're sourcing for 20+ roles simultaneously and don't have time for manual candidate discovery, AI automation is a force multiplier.

Competitive talent markets. When you're competing for candidates with every other company in your industry, passive candidate sourcing gives you access to people who aren't getting 50 InMails per week.

Diversity hiring goals. If you're struggling to build diverse pipelines through traditional sourcing, Arya's diversity features can help surface underrepresented candidates.

When Arya Is the Wrong Tool

Entry-level or high-volume commodity roles. If you're hiring customer service reps or sales development reps, you don't need 850M profile access. Job boards and LinkedIn active candidates will flood you.

Strong employer brand with inbound applications. If you're Google, Netflix, or another company where top candidates apply proactively, you don't need aggressive outbound sourcing.

Small recruiting teams with limited bandwidth. Arya surfaces candidates, but you still need to review them, personalize outreach, and manage conversations. If you can't handle the pipeline volume, sourcing more candidates makes things worse.

Companies prioritizing candidate experience. Mass automated outreach hurts candidate experience and employer brand if done poorly. If your brand depends on personalized recruiting, AI-sourced outreach is risky.

How to Use Arya Without Becoming a Spammer

The biggest risk with tools like Arya is turning into a recruiter everyone blocks. Here's how to avoid that:

Personalize outreach, don't automate it completely. Use Arya to find candidates, but write actual personalized messages referencing their specific background. "I saw your work on [specific GitHub project]" beats "You seem like a great fit for our team!"

Qualify candidates before reaching out. Just because Arya surfaces someone doesn't mean you should message them. Review profiles manually, confirm they're actually a fit, then reach out selectively.

Respect candidate preferences. If someone doesn't respond to outreach, don't follow up 5 times. Persistence is fine; harassment is not.

Focus on quality over volume. Reaching out to 20 highly qualified candidates with personalized messages works better than spamming 200 people with templates.

Be transparent about how you found them. "I found your profile through a sourcing platform that aggregates GitHub and LinkedIn data" is honest and respectful. Pretending you manually discovered them is weird.

How It Compares to Alternatives

vs. LinkedIn Recruiter: LinkedIn Recruiter has 1B profiles but limited search functionality and only shows active candidates. Arya has fewer profiles but better AI matching and multi-platform sourcing.

vs. Boolean Search (Manual Sourcing): Manual Boolean search on LinkedIn and GitHub is free but time-intensive. Arya automates this and adds machine learning. You're trading cost for time.

vs. SeekOut (Diversity-Focused Sourcing): SeekOut specializes in diversity sourcing and talent mapping. Arya has broader sourcing but less specialized diversity features.

vs. HireEZ (formerly Hiretual): HireEZ is another AI sourcing platform with similar multi-platform capabilities. Direct competitor to Arya. Feature sets are comparable; choice comes down to UX and pricing.

vs. Peoplebox Nova (AI Screening): Nova screens applicants you already have; Arya sources candidates you don't have yet. Different stages of the recruiting funnel, potentially complementary.

Arya's competitive advantage is the combination of massive profile access + machine learning matching + multi-platform aggregation in one tool.

Pricing and Implementation

Leoforce doesn't publish pricing publicly (shocking, I know). Expect enterprise-level pricing based on number of users, search volume, and features.

Implementation requirements:

• ATS integration (optional but recommended)
• Job descriptions and role requirements
• Outreach templates and messaging strategy
• Training on AI matching feedback loop

Setup timeline: 1-2 weeks for basic implementation, 4-6 weeks to fully optimize machine learning based on your feedback.

The Ethics Question Nobody's Asking

Is it ethical to aggregate 850 million people's data from multiple platforms and use it for recruiting outreach they didn't consent to?

Leoforce claims all data is publicly available and legally sourced, which is probably true. But "legal" and "ethical" aren't the same thing.

Candidates who put their GitHub profile online to showcase work or their Stack Overflow answers to help others might not appreciate that data being used for recruiting outreach. And while they "consented" by making profiles public, they didn't explicitly consent to AI aggregation and automated recruitment messaging.

This is a gray area. The recruiting industry has decided it's fine. Individual candidates might disagree.

Be thoughtful about how aggressively you use sourcing tools like this, and respect when people indicate they're not interested.

The Bottom Line

Arya is a powerful AI sourcing tool that gives you access to passive candidates across 850 million profiles. For hard-to-fill roles and competitive talent markets, that's genuinely valuable.

But access to massive candidate pools is only useful if you have the capacity to engage those candidates thoughtfully. Tools that make it easy to spam hundreds of people are dangerous in the wrong hands.

Use Arya for discovery, not for mass outreach automation. Let AI find candidates you wouldn't find manually, then engage them like a human being who cares about building relationships, not hitting activity metrics.

Rating: 7/10 (powerful sourcing, but requires discipline to avoid becoming a spammer)

Best for: Hard-to-fill specialized roles, high-volume recruiting teams, competitive talent markets, diversity hiring initiatives

Skip if: High-volume commodity roles, strong inbound candidate flow, small teams with limited bandwidth, companies prioritizing highly personalized candidate experience

Bottom line: 850 million profiles is impressive, but volume without quality and thoughtfulness is just noise. Arya gives you access to passive talent—what you do with that access determines whether it's a strategic advantage or an employer brand liability.