RChilli

Summary

RChilli is an AI parsing & matching engine that integrates with any data source, processing candidate data via cloud services (thereby not storing data), and profiling candidates for advanced matching to role requirements. Also developing data enrichment methodologies (enhancing analysis of the “context” of data to extrapolate further circumstantial information).

Product Highlights:

• Global services, offering a few focuses:

  • Parsing

    • Advanced parsing based on research and complex data identification & categorization methods

  • Matching engines

  • Enrichment Marketplace (not for government applications)

    • Data analytics

• Resume Parser

  • Extract contact details, education, experience, skills, social details (if available in resume)

  • Enrichment taxonomies (focused on competencies, skills, related skills, etc.)

  • Then moves to matching engine from there

  • In parsing, it identifies key information and produces tags for information like location, languages, skills, education, etc.

    • Can group into skills types too (technical, behavioural, soft, etc.)

    • Looking at behavioural assessments as an upcoming data point

      • Still working on this offering and developing it, assessing from language used, etc.

        • Behaviour matching is a growing theme of discussion in the HR field

    • Identifies and groups skills by proficiency levels assessed through the experience listed (job titles won’t identify proficiency, so this assesses content)

    • Can identify things like employment gaps (length of time, etc.)

    • Can also identify number of years of experience with certain skills (like management, for example)

  • Extremely detailed parsing and profile-building

• Matching Engine

  • Can search for what you need, such as industry, location, years of experience, or even paste a complete JD to see who best matches that JD

    • This is done by setting up an index for the JD, rather than a simple search, but then stays as a template for future use after that

  • Each candidate matched provides a detailed score breakdown for where they do/don’t fit the desire profile

  • Uses enriched data (ex. Can determine what “GTA” really means (what is or isn’t technically part of the GTA)

  • Taxonomy 3.0 Beta

    • Allows you to define each skill you’re analyzing for

    • Can be broader skills or more specific ones

      • Can also be tools they need to be familiar with

    • Set up related job titles

• Email Integration

  • Resumes can be submitted to an email that feeds them into the system

Technical Requirements:

• Typically ATS integrated (not mandatory)

• Can install into any data source we need (TN/TC/ATS, etc.) or be accessed via upload portal

Customization Options:

• Able to customize the profile information you’re looking for the parser to gather (what skills to identify, preferred versus mandatory)

• Customization of the platform’s features is also supported by a technical team for complicated requests (but basics can be done on our end perhaps)

  • Definitely not “foolproof” in a user-friendly context (intermediate software skills required)

Approach to Using with Multiple Clients:

• Sits on the primary ATS, but can be designed to function only with specific clients (functions with client ID)

• How data segregation between clients on one CRM/ATS could work

  • User keys

    • Each key creates a new access set up (each RC can have their own)

  • Small staffing companies use this to avoid RCs poaching other RCs candidates

GDPR/CCPA/Privacy Compliance:

• Does not store any data, it just sits over the system your data is located on

• As long as your data location is compliant, this system is compliant

• If it’s government, RChilli can facilitate arranging government data storage locations, and bills directly to you (decreases your business insurance)

• Page:
  Candidate.ID
• Page:
  Brazen
• Page:
  WayUp
• Page:
  PandoLogic
• Page:
  HiringSolved