RChilli’s Search & Match API, powered by Engine 3.0, is engineered for real-time, high-speed talent discovery, ensuring rapid and efficient processing of indexed resumes and job descriptions.
Query Execution Speed
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Built on cluster computing technology, the system is designed for instantaneous matching and ranking of the most relevant results.
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While specific performance metrics are not disclosed, the system consistently delivers real-time or near real-time responsiveness during typical search and match operations.
Underlying Technology Accelerating Query Performance
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Taxonomy & Ontology Mapping: Pre-enriches the data to support efficient keyword and concept-based searches.
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Preprocessed Facets and Filters: Index-level optimization minimizes runtime computation.
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AI/ML-Powered Search Engine: Context-aware parsing and semantic understanding reduce query complexity.
Facets and Filtering Documentation
Experience Range Deviation Guide
Real-World Performance Insights
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Designed to support enterprise-scale workloads, including bulk processing with pagination.
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Clients consistently report increased recruiter productivity and significantly reduced time spent on manual candidate filtering.
Pagination Handling in Search
Bulk Match Using Sub-User IDs
Special Performance-Boosting Features
| Feature | Description |
|---|---|
| Query Analyzer | Automatically interprets natural language into structured queries. |
| De-duplication Engine | Prevents redundant record processing, enhancing speed and accuracy. |
| Custom Weightage Logic | Dynamically configurable scoring that doesn't impact runtime performance. |
Estimated Query Performance (Qualitative View)
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Performance is consistently described as real-time across typical job-candidate matching use cases.
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RChilli’s infrastructure supports smooth, uninterrupted search operations, even under high data volumes.
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Factors like query complexity, payload size, and indexing load are intelligently managed to maintain responsiveness.
Summary
| Key Takeaway | Description |
|---|---|
| Search Efficiency | Designed for high-speed, real-time query execution |
| AI & NLP Capabilities | Delivers semantic, context-aware results |
| Backend Optimizations | Preprocessing, faceting, and clustering ensure system stability |
| Enterprise-Ready Architecture | Supports large-scale matching with consistent performance |
Need Deeper Benchmarking?
For advanced performance tuning, SLAs, or custom stress testing:
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Email: support@rchilli.com
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Visit: RChilli HelpDesk
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Explore API Docs: RChilli Developer Portal
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