Wipro Feedback & Learning Agent
Empower growth through continuous feedback and intelligent learning.
Publisher
Wipro
Product Details
This agent continuously improves candidate matching accuracy. It analyzes historical hiring outcomes to find patterns and suggests improvements, such as refining job description keywords, scoring, or verification criteria based on past successes and failures.
In its workflow, a large LLM performs causal analysis to identify key success factors, a smaller LLM updates skill vectors with new data, and a RAG system pulls historical hiring data to surface patterns. Together they keep the hiring model current and effective at finding high-potential candidates. Reported results include a 20% increase in retention, 15% lower hiring costs, 10% better performance, 25% faster onboarding, and 30% higher employee satisfaction for HR and recruitment teams.
Key Use Cases
Evidence-Based Job Description Tuning
Employs LLM-driven causal analysis across past employee tenures to recalibrate screening prompts, keywords, and minimum requirement scoring models.
Predictive Candidate-Role Fit Optimization
Continuously updates skill vector representations and uses RAG over past hiring datasets to elevate interview conversion and long-term retention rates.
Explore detailed deployment path
Requires Gemini. Access integration prerequisites, specialized agent configuration guides, and implementation documentation.