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Overview

The Filters Page in Asendia AI allows recruiters to refine and control the parameters of their candidate search.
After entering a natural-language prompt, the AI automatically generates filters based on the recruiter’s intent — these filters can then be reviewed, edited, or expanded before running the search.

Filter Categories

1. Job Role

Define the target position and related responsibilities.
The AI automatically detects and populates job titles, role keywords, and categories.
Example:
  • Job Role: Senior Full-Stack Engineer
  • AI-Generated Keywords: full-stack, engineer, architecture, cloud, web
  • Category: Technology
  • Function: Engineer
Recruiters can enter up to five roles per search, separated by commas, to expand sourcing coverage. Screenshot2025 10 21at8 22 15PM Pn

2. Location

Set geographic preferences and restrictions for candidates.
You can specify city, state, country, or choose remote-ready options.
Example:
San Francisco, CA · New York City · Remote (US-based)
The AI automatically includes nearby metropolitan areas if relevant to the search. Screenshot2025 10 21at8 22 26PM Pn

3. Experience

Define years of experience, seniority, and position level.
Common tiers include:
  • Entry-Level
  • Mid-Level
  • Senior
  • Lead / Principal
The AI also interprets phrases like “experienced in DevOps” or “junior backend engineer” directly from the recruiter’s input. Screenshot2025 10 21at8 22 38PM Pn

4. Skills & Keywords

Highlight the technical or domain skills required for the role.
The AI extracts these automatically and groups related concepts.
Example:
If the recruiter writes “React and Node.js engineer with cloud deployment experience”,
the filters might include:
  • React
  • Node.js
  • AWS / GCP
  • JavaScript / TypeScript
  • Cloud Infrastructure
Recruiters can add or remove skills manually at any time. Screenshot2025 10 21at8 22 48PM Pn

5. Company

Target candidates from specific companies or industries.
Useful for competitive sourcing, benchmarking, or identifying professionals from certain market sectors.
Example:
Amazon, Meta, Stripe, early-stage startups
Screenshot2025 10 21at8 22 57PM Pn

6. Education

Add filters for academic background, degree level, or field of study.
Example:
  • Degree: B.Sc. or higher
  • Field: Computer Science, Software Engineering, Data Science
  • Institution: optional filter (e.g., “top-tier universities”) Screenshot2025 10 21at8 23 09PM Pn

7. Additional Filters

Fine-tune your results using optional advanced filters such as:
  • Availability: Actively open to work / Passive candidates
  • Last Activity: Recently updated profiles
  • Languages: Spoken or programming languages
  • Visa / Work Authorization: When available from public data Screenshot2025 10 21at8 23 18PM Pn

AI-Generated vs. Manual Filters

Each filter begins as AI-generated from your natural language search.
Recruiters can then manually edit or remove filters to customize the search further.
Changes are instantly reflected in the matching and ranking process.
Screenshot2025 08 26at7 14 34PM Pn
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