**SkillShift** is a system designed to help employees and HR/Admins manage, explore, and retrieve organizational knowledge through **AI-assisted interactions**.
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Organizations often face operational and productivity risks when employees leave or move across teams without structured handovers or visibility into their unique knowledge, decisions, and expertise.
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This tool leverages **NLP-based knowledge mining** to automatically build a dynamic knowledge base and organizational decisions — all derived from communication channels like **Google Chat** and **Telegram**. The platform centralizes internal communication data, maintains tags for context classification, and provides employees and HR/Admins with an AI assistant to query messages and insights related to them or their assigned tags.
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In modern organizations, large volumes of valuable information — discussions, decisions, technical clarifications, and project context — are scattered across internal messaging tools. This tool provides a unified way to collect, organize, and retrieve such communication efficiently using AI-assisted search and tag-based categorization.
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Unlike traditional HR or knowledge base systems, this assistant focuses on **conversation intelligence** rather than static documentation. Instead of manually searching through thousands of chat messages, users can simply ask **natural language questions** through the AI assistant, which semantically understands the context and retrieves relevant messages tagged to their area, project, or topic.
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### Platform Users
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- **Employees**
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- View their profiles, assigned tags, and interact with the AI assistant to find relevant discussions or information.
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- **HR/Admins**
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- Manage and assign tags, configure data source integrations, and use the AI assistant for organization-wide insights.
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## 2. Objectives
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The system aims to achieve the following core objectives:
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- Consolidate organizational conversations from multiple data sources such as **Google Chat** and **Telegram** into a single, searchable knowledge base.
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- Simplify knowledge discovery through a **conversational AI assistant**.
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- Enable structured organization of communication via **tags** for projects, discussions, or themes.
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- Empower employees with **role-based access** to only relevant messages and topics.
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- Provide HR/Admins tools for efficient management of users, tags, and data sources.
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- Enhance organizational transparency and reduce information silos through AI-assisted knowledge retrieval.
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## 3. Initial Scope (MVP Deliverables)
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- **Integrations:** Google Chat & Telegram
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- **Screens:**
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- Employee Profile
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- AI Assistant
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- Tag Management
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- Data Source Management
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## 4. Users & Roles
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- **Employee:** View their profile and access the AI assistant.
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- **HR/Manager/System Admin:** Manage integrations and tag management.
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## 5. Architecture Overview
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*(Architecture diagram to be added in the final documentation.)*
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## 6. Module Breakdown
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### 6.1 Integration Layer
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- **Telegram Bot API:** Captures chat messages.
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- **Google Chat API:** Webhook/polling for spaces & groups.
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### 6.2 Processing & Embedding Layer
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- **Text Preprocessing:** Removes stopwords, links, emojis, and Personally Identifiable Information (PII).
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- **Embeddings:** Creates message text embeddings for semantic search.