"Recruit-AI" Development for Talent Acquisition

The Case Study: "Recruit-AI" Target User (Persona): • Sarah, a Talent Acquisition Manager or Founder at a 50-person tech company. She is overwhelmed by administrative tasks and fears missing out on great talent because resumes are buried in PDFs. • The Problem: High-volume resume screening leads to decision fatigue, slow time-to-hire, and poor candidate experience. • The Solution: An Agentic AI solution that automates the Screening & Scheduling phase of hiring. • Why Agentic AI: This problem requires parsing unstructured text (resumes and emails), making judgment calls based on job criteria, and taking actions such as scheduling. 2. Your Mission Phase 1: Discovery & Strategy • Market Research • Problem Framing • Process Documentation Phase 2: The Sales Pitch • Problem Hook • Market Opportunity • Solution Overview • Prototype • Technical Architecture • Roadmap & Financials • Success Metrics Phase 3: The Build (Frontend & Backend) Frontend: • Web interface to upload Job Description and Resume Backend (Agent): • Resume analysis against JD • Structured score (0–100) • Summary and Recommended Action • Optional calendar or email integration Integration: • Connect frontend and backend or document API handshake Phase 4: Demo & Reflection • 5-minute recorded walkthrough • Reflection on trade-offs, failures, and architecture decisions 3. List of Deliverables 1. Problem Framing Document (1–2 pages) 2. Pitch Deck (5–8 slides) 3. UX / Wireframes 4. Frontend Prototype Link 5. Backend Agent Workflow 6. Metrics & Roadmap Document (1 page) 7. Process & Decision Log 8. 5-Minute Video Pitch

N° de projet : 40249087