Neural_Core_Module_02
High-Dimensional
Semantic Reasoning.
Keywords are obsolete. Vetra maps candidate profiles into a 1,536-dimensional vector space, understanding the deep semantic relationship between skills, experience, and intent.
"React.js"
"Frontend Eng"
"UI Architecture"
Vector_Density
0.994 MATCH
Adjacency Mapping
Vetra recognizes that a "Senior Dev" in one company is equivalent to a "Staff Engineer" in another by analyzing context, not just job titles.
Intent Analysis
The engine identifies the trajectory of a candidate's career, scoring them higher if their recent roles show a clear path toward your open position.
Zero-Shot Search
Query your database in natural language. "Find someone who can build a high-scale fintech backend" works without SQL or complex filters.
Engine_Specifications.txt
Embedding Model Vetra-Semantic-v4 (1536d)
Query Latency < 45ms / 100k nodes
Bias Mitigation PII-Kernel Masking
Context Window Unlimited (Chunking)