Natural Language Search
Prompting tips, ranking, and run history.
Natural Language Search
Natural Language Candidate Search for Recruiting
Natural Language Search is the core way you interact with Beesla. Instead of building keyword queries or Boolean strings, you describe the role in plain English and Beesla returns ranked candidate results.
This page explains what Natural Language Search is, when to use it, and how it differs from traditional recruiting search tools.
What Natural Language Search Is
Natural Language Search allows you to search for candidates the same way you would explain a role to another recruiter or hiring manager.
You can:
- Write a short role description
- Paste a full job description
- Add preferences, priorities, or exclusions
Beesla reads this input as context and intent, not as a strict list of keywords.
How It Differs From Keyword Search
Traditional recruiting tools rely on:
- Keyword matching
- Boolean logic
- Resume formatting
- Exact phrase matches
Natural Language Search focuses on:
- Role intent
- Experience relevance
- Career context
- Signals beyond keyword density
This reduces resume spam and avoids rewarding candidates who optimize profiles for search engines instead of actual work.
What You Can Include in a Search
Natural Language Search works best when you include:
- Role title and seniority
- Core skills or technologies
- Relevant experience or industries
- Preferences and dealbreakers
Example:
Senior frontend engineer. Strong React experience. Has worked on consumer-facing products. Avoid frequent job changes.
You do not need to structure input or use special syntax.
Job Descriptions as Input
You can paste a full job description directly into the search.
This is useful when:
- You already have a finalized JD
- You want closer alignment to internal requirements
- You want sharper, more precise results
Many teams get the best results by pasting the job description and adding a short plain-English note with priorities or exclusions.
How Results Are Generated
When you run a Natural Language Search:
- Beesla retrieves candidate profiles
- Each profile is evaluated against your role description
- Candidates are scored and ranked
- Results are added automatically to your CRM
Each candidate returned by the search costs tokens based on the number of results returned.
When to Use Natural Language Search
Use Natural Language Search when you want to:
- Proactively source candidates
- Avoid inbound resume spam
- Build a shortlist quickly
- Evaluate candidates before outreach
It is designed for quality over volume.
Common Misconceptions
“I need to write a perfect prompt.”
You don’t. Clear and specific beats perfect.
“More text means better results.”
Only if it adds signal. Unnecessary detail can add noise.
“I need keywords.”
You don’t. Beesla handles interpretation automatically.
What’s Next
To improve result quality: