My Journey at Terabits Technolab: Building Real-World AI Products

My time at Terabits Technolab has been a transformative experience that pushed me from academic projects into building production-ready AI applications. Working on Auto-Reels and WhisperChat.ai taught me not just how to code, but how to architect, deploy, and scale real products that solve actual business problems.

Company Overview

Terabits Technolab is a technology solutions provider focused on:

• AI-powered business applications
• Custom software development
• Enterprise system integration
• Digital transformation consulting

My Role and Learning Path

As a developer at Terabits, I progressed through multiple domains while building two flagship AI products from concept to deployment.

Major Projects Built

Auto-Reels: AI Video Generation Platform

Built a complete AI-powered video creation platform that generates viral-ready content for Instagram Reels and TikTok.

Core Features Developed

• Hook + demo video generation system
• Greenscreen meme video creator
• Content to avatar video conversion using HeyGen
• AI slideshow generation from images

Technical Implementation

• Frontend: Next.js with TailwindCSS and Canvas-based video preview
• Backend: Odoo for workflow management and business logic
• Processing: FFmpeg for video encoding and manipulation
• Storage: Cloudflare R2 for assets and CDN delivery
• Database: PostgreSQL for metadata and project storage

WhisperChat.ai: Document-Based Chatbot Platform

Created an intelligent chatbot platform that transforms documents and websites into conversational AI assistants.

Core Features Developed

• Multi-format document upload (CSV, PDF, TXT, DOCX)
• Website URL crawling and content extraction
• Custom chatbot branding and theming
• Flexible embedding options (floating bubble and iframe)
• Conversation analytics dashboard
• Knowledge base management system

Technical Implementation

• Frontend: Next.js, TailwindCSS, TanStack Query with Gumroad-inspired design
• Backend: Odoo for user management and chatbot configuration
• AI: ChatGPT API for conversational responses
• Vector Database: pgvector extension in PostgreSQL for semantic search
• Embeddings: OpenAI embeddings for document understanding

Skills Acquired

Odoo ERP Development

Learning Odoo was the foundation of both projects:

Core Concepts Mastered

• MVC architecture and ORM usage
• Custom module development
• Workflow automation and business logic
• User authentication and permissions
• Database migrations and upgrades

Practical Applications

• Built subscription management systems
• Developed project and asset management modules
• Implemented payment processing workflows
• Created analytics aggregation systems
• Designed custom API endpoints

Multi-Version Management

• Set up isolated virtual environments for different Odoo versions
• Managed version-specific dependencies
• Handled database compatibility across versions

Web Development

Frontend Mastery

• Next.js: Server-side rendering, API routes, dynamic routing
• TailwindCSS: Utility-first styling and responsive design
• Canvas API: Real-time video preview rendering
• State Management: TanStack Query for efficient data fetching

API Development

• RESTful API design principles
• Authentication and authorization
• Rate limiting and error handling
• Webhook integrations
• Third-party API integration (HeyGen, ChatGPT, OpenAI)

DevOps and Deployment

Server Management

• Linux server administration
• Nginx configuration and reverse proxy setup
• SSL certificate management
• Performance monitoring and optimization

Containerization with Docker

• Writing efficient Dockerfiles
• Multi-stage builds for optimization
• Docker Compose for multi-container applications
• Image management and registry usage
• Container networking and volumes
• Troubleshooting deployment issues

Deployment Platforms

• Dokploy: Self-hosted PaaS platform deployment
• Coolify: Open-source deployment automation
• CI/CD pipeline configuration
• Environment variable management
• Database backup strategies
• Zero-downtime deployment techniques

Infrastructure Tools

• Git for version control and collaboration
• PM2 for Node.js process management
• PostgreSQL administration and backup
• Cloudflare configuration for CDN and storage

Challenges Overcome

Scaling Video Processing

Auto-Reels required handling multiple concurrent video generation requests. I learned to implement queue-based processing and optimize FFmpeg parameters for faster rendering without quality loss.

Vector Search Performance

WhisperChat.ai needed sub-second response times for semantic search. Implementing pgvector with proper indexing strategies and chunk size optimization solved this challenge.

Multi-Platform Deployment

Deploying complex applications with multiple dependencies taught me the importance of containerization and proper environment configuration. Docker became essential for consistent deployments.

Odoo Customization

Extending Odoo to handle AI workflows required deep understanding of its module system and database architecture. I learned to work within Odoo's constraints while building custom functionality.

Key Learnings

Architecture Decisions Matter

Choosing Odoo as the backend framework provided built-in user management and workflows but required learning its conventions. This taught me to evaluate tradeoffs between custom solutions and established frameworks.

DevOps is Essential

Understanding deployment, monitoring, and scaling is as important as writing code. Learning Docker and deployment platforms made me a more complete developer.

AI Integration Complexity

Working with multiple AI APIs (ChatGPT, HeyGen, OpenAI embeddings) taught me about API reliability, cost optimization, and building robust error handling for external dependencies.

User Experience Focus

Both projects required intuitive interfaces for non-technical users. This shifted my focus from "what's technically impressive" to "what solves the user's problem simply."

Technical Growth Metrics

Before Terabits

• Basic web development knowledge
• Limited backend experience
• No production deployment experience
• Minimal DevOps understanding

After Terabits

• Full-stack development with modern frameworks
• Enterprise ERP customization
• Production AI application deployment
• Docker and containerization proficiency
• Server management and DevOps skills

Tools and Technologies Mastered

Development Stack

• Frontend: Next.js, React, TailwindCSS, Canvas API
• Backend: Odoo, Node.js, Python
• Databases: PostgreSQL, pgvector
• AI/ML: ChatGPT API, OpenAI embeddings, HeyGen
• Processing: FFmpeg, text extraction libraries

DevOps Tools

• Containerization: Docker, Docker Compose
• Deployment: Dokploy, Coolify
• Web Servers: Nginx
• Monitoring: Server logs, application metrics
• Version Control: Git, GitHub

Cloud Services

• Storage: Cloudflare R2
• CDN: Cloudflare
• Hosting: Self-hosted servers, cloud platforms

Impact and Results

Auto-Reels

• Automated video generation reducing production time by 80%
• Processing multiple video formats and styles
• Deployed and serving users with reliable performance

WhisperChat.ai

• Instant chatbot creation from documents
• Sub-second response times with semantic search
• Scalable architecture handling concurrent users

Future Aspirations

Building on this foundation, I plan to:

• Contribute to open-source Odoo modules
• Explore advanced AI integrations and custom model training
• Master Kubernetes for orchestration at scale
• Build more AI-powered products
• Share knowledge through technical writing and tutorials

Gratitude

I'm grateful to Terabits Technolab for providing the opportunity to work on cutting-edge AI projects. The hands-on experience with real products, combined with the freedom to explore different technologies, has been invaluable for my professional growth.

Reflection

My journey at Terabits Technolab has been more than just learning technologies - it's been about understanding how to build complete products that solve real problems. From initial concept to deployed application, I've experienced the entire development lifecycle while working with modern AI technologies.

The combination of building two distinct AI products (video generation and conversational AI) gave me diverse experience in different domains. Learning Odoo as the backbone for both projects taught me to leverage existing frameworks effectively. Mastering DevOps and deployment platforms transformed me from a developer who writes code to one who can ship and maintain production systems.

This experience has prepared me not just to code, but to architect, deploy, and scale AI applications - skills that are essential in today's technology landscape.