Project: SkillShift

Tagline: Ensuring that when employees leave, change roles, or new hires join, no expertise is lost.

👥 Team: Teams/Team Orbit

📌 Status: 🟡 Planning

🔎 Overview

SkillShift is an AI-powered shifting skills seamlessly across roles that automatically captures, organizes, and transfers critical knowledge within an organization.
👉 Ensuring that when employees leave, change roles, or new hires join, no expertise is lost and knowledge is instantly accessible.

✨ Key Characteristics

1. 📝 Always-On Knowledge Capture
2. 🤖 AI-Powered Summarization & Q&A
3. 🔗 Knowledge Graph of People, Projects, and Decisions
4. 📦 Automated Handover Packages
5. 📊 Succession Planning & Risk Insights
6. 🚀 Onboarding Accelerator

❌ The Problem

1. Huge knowledge loss when employees resign or switch roles.
2. New hires take weeks/months to ramp up due to scattered tribal knowledge.
3. Single points of failure: only one person knows a critical system.
4. Past decisions buried in Jira/Slack → teams reinvent solutions.
5. No visibility for leaders into knowledge distribution.
6. Manual documentation is outdated and inconsistent.
7. Experts are overloaded answering repetitive questions.

💡 Our AI Solution

✅ What does it do?

• For Employees: Smooth onboarding, faster learning, less frustration.
• For Teams: Reduced dependency on single experts, better collaboration.
• For Managers: Clear risk visibility, succession planning, workforce insights.
• For Organizations: Preserve IP, resilience, and smoother transitions.

⚙️ How does it work?

🏗️ Architecture

• Data Sources → Docs, chat tools
• Data Processing → ETL pipelines, skill/role normalization
• Knowledge Graph → employees ↔ skills ↔ roles ↔ successors
• AI Layer →
  • NLP for skill extraction/matching
  • ML for attrition risk & readiness scoring
  • LLM chatbot for Q&A
• App Layer → dashboards, chatbot, alerts (Google Chat/Telegram)

🔄 Data Flow

1. Collect & clean data from various sources
2. Build knowledge base of roles, skills, projects, etc.
3. Run AI models → risk prediction & readiness scoring
4. Deliver insights via dashboards + chatbot

🚀 What makes it innovative?

1. Captures knowledge beyond HR data → chats, code, unstructured docs.
2. Automated handover with AI-clone / chatbot of past work.
3. Visual knowledge graph showing ownership & linking artifacts.
4. Continuous ingestion & updates (vs periodic HR efforts).
5. Contextual Q&A over actual work (vs static profiles).

🛠️ Technology Stack

• NLP/LLM: OpenAI (GPT-4), LLaMA
• Framework & Libraries: LangChain
• Frontend: React.js + Tailwind (dashboards, chatbot UI)
• Backend: FastAPI (Python) + JWT auth
• Database: PostgreSQL (pgvector) + Elasticsearch
• Integrations: Telegram Bot API, Google Chat API
• Deployment: Docker + GitLab CI/CD (EC2/DigitalOcean)

🏗️ Project Architecture

graph LR
    A[📂 Data Sources → Chats, Docs, Code ] --> B[⚙️ Data Ingestion Pipelines → APIs, ETL, LLM extractors]
    B --> C[🗄️ Knowledge Store → Postgres + pgvector + ElasticSearch]
    C --> D[🔗 Knowledge Graph → Employees ↔ Projects]
    D --> E[🤖 AI Services Layer, LLM Q&A - LangChain, Succession Risk, Handover Gen]
    E --> F[💻 Client Interfaces, Web Dashboards - React, Chatbot - Telegram/GC ]

🧩 Challenges & Learnings

To be added during development phase

📅 Future Roadmap

• Short-term (MVP):

  • Integration with Google Chat & Telegram
  • AI-powered chatbot for Q&A
  • Handover Package Generator
  • Dashboards: Employee Profiles & Succession Pipeline Dashboard

• Medium-term: To be added

• Long-term: To be added

📂 Repository & Demo

• GitHub Repository: 🔜 Coming Soon
• Live Demo: 🔜 Coming Soon

📸 Screenshots / Demo Video

🔜 Will be shared in next milestone

🏷️ Categories

#project #ai-hackathon-2025 #HR #SuccessionPlanner