What is RChilli SearchEngine Indexing and Search Capacity?

RChilli SearchEngine Indexing

Indexing in the RChilli context refers to how structured resume or job data is stored in a searchable format to enable real-time and intelligent search functionalities.

Key Features of Indexing:

• Temporary Data Storage: While the Resume Parser API does not store data, the Search and Match API temporarily stores indexed documents in a secure, region-specific environment for search and match operations.

• Search-Ready Format: Indexed data includes enriched and normalized fields such as skills, job titles, education, companies, and location, formatted to power fast and accurate searches.

• Data Control: Users can delete all indexed documents using the /deleteAllDocuments API endpoint when a clean slate is needed.

• Region Specificity: Indexes are stored based on the region selected by the customer (e.g., US, EU, Asia), which supports compliance and optimal performance.

• Indexing vs. Parsing: Parsing extracts and structures the data, while indexing makes that data searchable. To perform both together, use the ParseAndIndex API.

Search Capacity (Search & Match Engine)

RChilli’s Search & Match Engine 3.0 is a high-performance, AI-powered engine optimized for bulk search and real-time matching capabilities.

Core Functionalities:

• Document-Based Search: Enables users to match:

  • Job to Job (J2J)

  • Resume to Resume (R2R)

  • Resume to Job (R2J)

  • Job to Resume (J2R)

• Semantic Search Engine: Uses intelligent query expansion and taxonomy mapping to improve relevance. Keywords are tagged and categorized into facets like:

  • Location

  • Company

  • Tools/Skills

  • Job Titles

• Advanced Filters: Includes faceting, range filters (like years of experience), and dynamic scoring.

• Custom Scoring: Users can adjust weightage (e.g., skills 60%, location 10%) from the front-end to influence API results.

• Pagination and Bulk Data Processing: Built to process high volumes of resumes or job descriptions using pagination for performance optimization.

• Security: All operations are GDPR-compliant, with secure API access and data control capabilities.

Performance Highlights

• Cluster Computing: RChilli's Search Engine 3.0 uses lightning-fast cluster technology to enable real-time results even in high-volume use cases.

• Top 10 Match Ranking: Returns a ranked list of the most relevant candidates or jobs instantly.

• Support for Bulk Uploads: Efficient handling of large datasets, ideal for enterprise-scale hiring.

Indexing Locations and Data Centers

• Indexed data is stored and processed based on the data center chosen at setup (e.g., Phoenix, Frankfurt, Singapore).

• Search and Match operations currently run from the USA server only.

Summary