Stripped down readme to minimal details with updated stack

README.md

@@ -1,20 +1,15 @@
-# An Agentic Approach to Domain-Specific Trainers
+# An Agentic Approach to Domain-Specific Trainers - Dynavera
 
 A proof-of-concept platform for **automating the induction and support of new hires or team members** into a role or domain using **AI agents**. This project demonstrates a reusable workflow that combines a modern full-stack application with AI-driven guidance and assessment.
 
-Tentative app name: Dynavera
-
 ---
 
 ## Table of Contents
 
 -   [Project Goals](#project-goals)
 -   [Tech Stack](#tech-stack)
-- [Architecture](#architecture)
 -   [Features](#features)
-- [Setup](#setup)
 -   [Usage](#usage)
-- [License](#license)
 
 ---
 
@@ -31,11 +26,12 @@ The main objectives of this project are:
 
 ## Tech Stack
 
-- **Backend:** [NestJS](https://nestjs.com/)
+-   **Backend:** [Django](https://www.djangoproject.com/)
 -   **Frontend:** [Vue 3](https://vuejs.org/) + [Vite](https://vitejs.dev/)
-- **AI Agents:** Python or JavaScript (TBD)
+-   **AI Agents:** Python-based agents (TBD)
+-   **Containerization:** Docker + Docker Compose
 -   **Database:** (TBD)
-- **Authentication:** JWT / OAuth2 / Custom Managed
+-   **Authentication:** JWT / OAuth2 / Custom Managed (TBD)
 
 ---
 
@@ -50,12 +46,6 @@ The main objectives of this project are:
 
 ---
 
-## Setup
-
-TBC
-
----
-
 ## Usage
 
 1. Navigate to the frontend URL (hosted at `https://project.viswamedha.com`).
@@ -63,9 +53,3 @@ TBC
 3. Select the role/domain to train in.
 4. Follow the guided AI-assisted onboarding workflow.
 5. Track progress and view recommendations on the dashboard.
-
----
-
-## License
-
-[MIT License](LICENSE)