Commit 0d74de

2025-09-25 06:44:16 Sayali Mahajan: Done
Projects/AnswerVault.md ..
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<center><h1>πŸš€ AnswerVault</h1></center>
- # Project: AnswerVault
+ # Project: **AnswerVault**
- **Tagline:** Ensuring that when employees leave, change roles, or new hires join, no expertise is lost.
+ **Tagline:** _Ensuring that when employees leave, change roles, or new hires join, no expertise is lost._
- **Team:** [Team Orbit](https://wiki.enovate-it.com/Teams/Team%20Orbit)
- **Project Status:** 🟑 Planning
+ πŸ‘₯ **Team:** [Team Orbit](https://wiki.enovate-it.com/Teams/Team%20Orbit)
+ πŸ“Œ **Status:** 🟑 Planning
## πŸ”Ž **Overview**
- **AnswerVault** is an **AI-powered knowledge continuity platform** that automatically captures, organizes, and transfers critical knowledge within an organization.
- πŸ‘‰ This ensuring that when employees leave, change roles, or new hires join, no expertise is lost and knowledge is instantly accessible.
- #### ✨ **Key Characteristics:**
+ **AnswerVault** is an **AI-powered knowledge continuity platform** that automatically captures, organizes, and transfers critical knowledge within an organization.
+ πŸ‘‰ Ensuring that when employees leave, change roles, or new hires join, no expertise is lost and knowledge is instantly accessible.
+
+ ### ✨ **Key Characteristics**
1. πŸ“ Always-On Knowledge Capture
2. πŸ€– AI-Powered Summarization & Q&A
3. πŸ”— Knowledge Graph of People, Projects, and Decisions
@@ 24,38 25,37 @@
## ❌ **The Problem**
- 1. When an employee resigns or changes roles, a huge chunk of undocumented knowledge leaves with them.
- 2. New hires take weeks or months to β€œramp up” because tribal knowledge is scattered.
- 3. Often only one person knows a critical system β†’ single point of failure.
- 4. Teams reinvent solutions because past decisions are hidden in Jira or buried in Slack.
- 5. Leaders don’t have visibility into who holds what knowledge.
- 6. Manual documentation is boring, outdated, and nobody does it consistently.
+ 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 β†’ 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 Manual documentation is outdated and inconsistent.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.
---
## πŸ’‘ **Our AI Solution**
- #### βœ… **What does it do?**
- 1. **For Employees:** Smooth onboarding, less frustration, faster learning.
- 2. **For Teams:** Less dependency on single experts, better collaboration.
- 3. **For Managers:** Clear risk visibility, succession planning, workforce insights.
- 4. **For Organizations:** Preserve IP, resilience, smoother transitions.
-
-
- #### βš™οΈ **How does it work? **
-
- ##### πŸ—οΈ Architecture
- - **Data Sources** β†’ HRMS, LMS, reviews, chat tools
- - **Data Processing** β†’ ETL pipelines, skill/role normalization
- - **Knowledge Graph** β†’ employees ↔ skills ↔ roles ↔ successors
- - **AI Layer** β†’
- - NLP for skill extraction/matching
- - ML for attrition risk & successor readiness
- - LLM chatbot for Q&A
- - **App Layer** β†’ dashboards, chatbot, alerts (Google Chat/Telegram)
-
- #### πŸ”„ **Data Flow**
+ ### βœ… **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.
+
+ ### βš™οΈ **How does it work?**
+
+ #### πŸ—οΈ Architecture
+ - **Data Sources** β†’ HRMS, LMS, reviews, chat tools
+ - **Data Processing** β†’ ETL pipelines, skill/role normalization
+ - **Knowledge Graph** β†’ employees ↔ skills ↔ roles ↔ successors
+ - **AI Layer** β†’
+ - NLP for skill extraction/matching
+ - ML for attrition risk & readiness scoring
+ - LLM chatbot for Q&A
+ - **App Layer** β†’ dashboards, chatbot, alerts (Google Chat/Telegram)
+
+ #### πŸ”„ **Data Flow**
1. Collect & clean HR/learning/performance data
2. Build knowledge graph of roles & skills
3. Run AI models β†’ risk prediction & readiness scoring
@@ 63,25 63,25 @@
---
- ### πŸš€ **What makes it innovative?**
+ ## πŸš€ **What makes it innovative?**
- 1. Deeper knowledge capture (not just HR data, also chats, code, unstructured docs).
- 2. Automated handover + AI-clone / chatbot of past work.
- 3. Detailed knowledge graph showing who owns what modules, and linking artifacts.
- 4. Continuous ingestion & update rather than periodic HR efforts.
- 5. Contextual Q&A over actual work vs static competency profiles.
+ 1. Captures knowledge beyond HR data β†’ 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).
---
- ## πŸ› οΈ **Technology Stack**
+ ## πŸ› οΈ **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 as a vector DB/Elasticsearch
+ - **Database:** PostgreSQL (pgvector) + Elasticsearch
- **Integrations:** Telegram Bot API, Google Chat API
- - **Deployment:** Docker + GitLab CI/CD (EC2/DigitalOcean for hosting)
+ - **Deployment:** Docker + GitLab CI/CD (EC2/DigitalOcean)
---
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