Your candidate database is your most valuable asset. However, for many recruiting teams, it is also the most underutilized. As your database grows, traditional search tools struggle to keep up, often forcing you to rely on rigid keyword queries that miss high-potential talent simply because a resume doesn't match your exact search terms.
Today, we are launching the AI Recommendation Engine in Public Beta. This feature moves beyond simple keyword matching to understand the meaning behind a job description. It reads your requirements like a human recruiter would, instantly surfacing the best candidates from your existing pool.
This moves sourcing beyond the limitations of exact keyword matching and delivers a ranked shortlist of candidates who fit the actual requirements of the role.
Ready to try it? Book a demo here >>
Moving Beyond the Keyword Trap
Most Applicant Tracking Systems force you to behave like a machine. You spend hours crafting complex Boolean strings and guessing which keywords a candidate might have used.
This shifts your workflow from manual hunting to intelligent review.
How It Works
Manatal’s AI Recommendations now automates the analysis of your job descriptions and your candidate database to improve sourcing accuracy.
1. Intelligent Requirement Extraction
Stop building complex filter sets manually. When you save a job description (optimally 150+ words), the system automatically reads the role. It extracts the core requirements and categorizes them into Required and Preferred qualifications.
2. Semantic Search
The engine scans your entire database, including past applicants you may have missed. It matches based on meaning, not just keywords.
Example: If you are hiring for a "SaaS Sales Manager," the AI knows to look for "B2B Software Sales" experience. It finds qualified candidates that rigid keyword searches would ignore.
3. Transparent Scoring and Justification
We believe AI tools should be explainable. Every recommended candidate comes with an AI Match Overview that includes:
- Match Score: A clear percentage indicating fit.
- Justifications: Line-by-line explanations of why a candidate matches specific requirements (e.g., "Has 4.5 years in project management within the tech industry").
- Gap Analysis: Immediate visibility into which preferred skills are missing.
4. Precision Control
Not every requirement carries equal weight. With the new weighting tool, you can assign specific levels of importance to your requirements.
This gives you granular control to fine-tune exactly how candidates are ranked, ensuring the AI prioritizes the skills that matter most to your specific role.
When to Use the AI Recommendation Engine
This feature is designed to support high-value recruitment scenarios:
- Candidate Rediscovery: Instantly surface a "Silver Medalist" from a role you filled two years ago who is now a perfect match for a new opening.
- High-Volume Screening: When you receive 500 applicants or more, the AI ranks them by fit. This allows you to focus your manual review on the top candidates immediately.
- Niche Role Sourcing: Find candidates with specific, hard-to-define skill sets that simple keyword searches often fail to capture.
Why This Matters for Your Bottom Line
We built this engine to solve specific operational inefficiencies. It delivers immediate value in three ways:
1. Maximize the ROI of Your Database
Every candidate in your system cost money to acquire, whether through job board ads, LinkedIn outreach, or marketing spend. When you cannot find them again for new roles, that investment is underutilized.Our engine scans your entire history of past applicants. It allows you to fill new openings using talent you already own, significantly reducing your reliance on expensive external job postings.
2. Reduce Time-to-Shortlist
Screening is the biggest bottleneck in high-volume hiring. Instead of reviewing hundreds of resumes to find a handful of matches, the AI provides an immediate, ranked shortlist. You start your day reviewing the top 10% of candidates who are already qualified, rather than filtering out the 90% who aren't.
3. Eliminate the "False Positive" Time Sink
Standard search tools often return candidates who match a keyword but lack the context (e.g., a "Project Manager" appearing in a search for a "Product Manager"). Our engine analyzes experience, education, and skills in context, ensuring you only spend time reviewing viable profiles.
Join the Public Beta
The AI Recommendation Engine is available now in Public Beta.
New to Manatal? Click here to start your 14-day free trial to transform the way you recruit today.
Ready to upgrade your sourcing? Log in to Manatal, navigate to any job, and let the AI turn your job description into your next hire. Read the documentation >>
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