📘 Candidate Search in KeyPartners Database using AI

📖 What is AI Advanced Search?

AI Advanced Search is an intelligent search tool that allows you to find candidates in the Key Partners database using advanced multiple criteria. The AI system analyzes profiles and returns results with match percentage, ranking candidates by relevance to the specified criteria.

This search works ONLY on:

  • ✅ Candidates already present in the KeyPartners database
  • ❌ Does NOT search on LinkedIn or external platforms

🎯 Objective

Use AI search to quickly identify the most suitable candidates for a specific position, applying multiple selection criteria and displaying the compatibility degree of each candidate.

This functionality is essential because:

✅ Intelligent search - AI analyzes and classifies candidates by relevance

✅ Multiple criteria - Combine skills, education, experience, location

✅ Match scoring - Percentage indicates compatibility degree

✅ Maximum efficiency - Find ideal candidates in just a few clicks

✅ Internal database - Leverage already available resources



🔍 PART 1: How to Search in the KeyPartners Database Using AI Advanced Search


1. Open the Candidates section

  • From the home page, select "Candidates" in the left sidebar
  • The complete list of candidates in the database opens

2. Locate the AI Search button

  • At the top of the page, locate the "AI Advanced Search" button
  • Click on "AI Advanced Search"
  • A side panel opens on the right side of the page (This is the panel to configure AI search criteria)

3. Start adding a criterion

  • In the right side panel, click on "New Criteria"
  • A dropdown menu opens with available criteria types

5. Select the type of criterion, e.g.: Select "Skills" from the dropdown menu

6. Enter the criterion value

  • Select Required/Preferred/Must Not (see Part 2 of this article to better understand the meaning)
  • In the selected field enter the values to search
  • Example for Skills: HTML, Python, React  
  • Possible to enter multiple values

7. Save the first criterion

  • After configuring the first criterion (e.g. Skills):
    • Click "Apply"
    • The criterion is saved in the panel
    • Remains visible in the active criteria list

8. Add additional criteria

  1. Click again on "New Criteria"
  2. Select a new type (e.g. "Education")
  3. Enter desired values (e.g. Master Degree, Computer Science   )
  4. Select Required/Preferred/Must Not
  5. Click "Apply"

Repeat the process for all necessary criteria.

9. Start the AI search

Once all desired criteria have been added:

  • Click "Apply" (button at bottom right)
  • The AI system processes the criteria
  • Returns the list of candidates that match

10. Modify criteria

If results are not satisfactory:

  1. Click again on "Criteria" in the side panel
  2. Modify existing criteria:
    • Change from Required to Preferred (broaden results)
    • Change from Preferred to Required (narrow results)
    • Modify entered values
  3. Add new criteria to filter further
  4. Remove overly restrictive criteria
  5. Click "Apply" to re-run the search

👁️ PART 2: Actions on Found Candidates

11. View candidate profile

  • Next to the candidate's name, locate the eye icon 👁️
  • Click on the eye icon
  • The candidate's complete profile opens with all details:

12. Associate candidate with a JOB

  • Locate the "Add to Job" button for the desired candidate
  • Click on "Add to Job"
  • Select the specific Job from the menu
  • Confirm the addition
  • The candidate enters the pipeline of the selected Job

When to use:

  • Perfect candidate for open position
  • Manual addition to pipeline
  • Proactive sourcing from database
  • Note: in this case the candidate will not be notified of entering a selection process and will not receive the privacy email until it is sent manually

🔍 PART 3: Interpreting the % displayed in search results

13. Interpret results

Results display:

  • List of candidates ordered by relevance
  • Each candidate also shows Match percentage (e.g. 95%, 87%, 72%), What the percentage indicates:
    • 90-100%: Excellent match - Ideal candidate
    • 70-89%: Good match - Valid candidate with some gaps
    • 50-69%: Average match - Candidate to evaluate carefully
    • <50%: Low match - Probably not suitable

How it's calculated:

  • AI algorithm evaluates how many Required criteria are satisfied
  • How many Preferred criteria are present
  • Weight of Must Not criteria (if violated, % drops)
  • Combination and overall relevance

14. Meaning of REQUIRED, PREFERRED, MUST NOT


1️⃣ REQUIRED ✅ (Mandatory)

Meaning:

  • The candidate MUST have this skill/characteristic
  • Candidates without this requirement will NOT be shown in results

When to use:

  • Essential technical skills
  • Mandatory certifications
  • Non-negotiable requirements

Example:

  • Required: Python, React  
  • Result: Only candidates with BOTH skills

2️⃣ PREFERRED 💡 (Preferred)

Meaning:

  • Candidate with this skill is favored in ranking
  • Candidates without this requirement are still shown, but with lower match %
  • It's not an exclusive filter

When to use:

  • Desirable but not essential skills
  • "Nice to have"
  • Characteristics that improve the profile

Example:

  • Preferred: Docker, Kubernetes  
  • Result: All candidates shown, those with Docker/Kubernetes have higher %

3️⃣ MUST NOT ❌ (Must not have)

Meaning:

  • The candidate must NOT have this skill/characteristic
  • Candidates with this requirement are excluded from results

When to use:

  • Exclude over-qualified profiles
  • Avoid conflict of interest (e.g. ex-employees of competitors)
  • Filter out unwanted skills

Example:

  • Must Not: Management experience  
  • Result: Candidates with managerial experience excluded
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