Streamline recruitment with AI-driven resume parsing, semantic matching, and interactive candidate Q&A — ensuring the best talent fit and bias reduction.
Leverage OpenAI, Azure AI, and Graph/RAG models for resume ingestion, scoring, and matchmaking. Visualize relationships and fill rate via interactive graph UI built with Angular, Flask, and LangChain.
Key Features
- ✔ Automated resume parsing, key skill/entity extraction
- ✔ Job description analysis and semantic matching
- ✔ Candidate scoring, ranking and interview readiness assessment
- ✔ Graph-based analysis and Q&A with Neo4j integrations
- ✔ Bulk and real-time workflow support with ATS/HRM integration
Benefits
- 🎯 Reduce time-to-hire and effort in talent screening
- 🎯 Improve job-candidate fit accuracy and team match
- 🎯 Reduce human review bias, increase transparency
- 🎯 Enable interactive and data-driven hiring processes
Real-World Use Cases
- Bulk resume processing and shortlist automation for HR/recruiters
- AI chatbots to interact with candidate resumes and answer hiring manager queries
- Diversity hiring, rating standardization, and reporting
- Graph-based visual search across candidate pools
