Enterprise HR Automation & Local RAG Platform
An end-to-end recruitment intelligence system featuring automated CV collection, candidate scoring, dynamic CV generation, and local RAG capabilities deployed on Kubernetes with automated observability and evaluation quality gates.
Business Challenge
Manual CV screening and candidate evaluation create significant bottlenecks in HR workflows. HR teams spend excessive hours manually collecting resumes, parsing unstructured PDF data, scoring candidate qualifications against job criteria, and reformatting resumes into standardized corporate templates. Additionally, lack of automated deployment and observability in model workflows leads to slow iteration cycles and potential downtime.
Solution Delivered
Built an end-to-end AI-powered HR automation and Local RAG platform. The system automatically ingests CVs submitted via web forms, extracts structured candidate details using OpenAI/Ollama LLM agents, and logs applicants directly into tracking databases. It dynamically scores candidates against job specifications (age, experience, skills) and generates standardized client-ready CV documents in Word format. Deployed on Kubernetes, the platform features automated gated rollouts (Blue/Green), evaluation quality gates, and full-stack monitoring via Prometheus and Grafana.
Outcomes Achieved
Operational Efficiency & Productivity: Accelerated the candidate screening and selection cycle by automating manual CV extraction, scoring against job requirements, and auto-generating standardized resumes. Quality & Knowledge Management: Standardized resume formatting across candidate profiles and integrated a Local RAG system to enable fast, context-aware information retrieval from internal HR datasets. Deployment Reliability: Improved AI performance and deployment speed by establishing a Kubernetes-based CI/CD architecture with automated evaluation quality gates and full-stack observability.
Measurable Business Outcome
Automated CV processing and candidate scoring by 80%, reducing candidate evaluation turnaround time from days to minutes while standardizing 100% of generated candidate profiles.