Anas Kaithakoden's Work | ContraWork by Anas KaithakodenAnas Kaithakoden
AI Automation Systems for Real Business Workflows
Built an AI-powered voice receptionist system capable of handling real-time phone conversations, answering customer questions, and assisting with appointment booking workflows.
The system combines speech-to-text, large language models, and text-to-speech technologies to create natural voice interactions over phone calls.
Key contributions:
• Built a real-time voice conversation workflow for handling inbound customer calls
• Integrated speech-to-text processing for live voice transcription
• Used AI language models to generate context-aware conversational responses
• Implemented text-to-speech voice generation for natural AI responses during calls
• Developed multi-turn conversation flows for collecting customer information and appointment details
• Built backend logic to manage conversation state and call workflows
• Worked on browser-based softphone integration for handling calls through the web
Tech stack:
• Python
• Flask
• Twilio
• Whisper
• Groq / Llama 3
• ElevenLabs / Edge-TTS
• AI Conversation Systems
• Voice Automation
This project strengthened my experience in voice AI systems, conversational workflows, speech processing, and real-time automation for customer communication. Developed a data extraction system using Python and Selenium to collect and organize structured business data from web sources.
The project focused on automating large-scale restaurant data collection while handling dynamic website content and multi-page navigation reliably.
Key contributions:
• Built automated scraping workflows using Python and Selenium
• Extracted restaurant and business data from multiple pages and dynamic web elements
• Handled pagination and browser interactions for reliable large-scale data collection
• Cleaned, organized, and structured extracted data into CSV format for analysis and business use
• Improved efficiency by automating repetitive manual data collection tasks
Tech stack:
• Python
• Selenium
• CSV Data Processing
• Web Scraping
• Browser Automation
Result:
Delivered organized datasets ready for analysis, reporting, and operational use. Built a fully automated multi-platform content publishing system that transforms a single Telegram video into ready-to-publish content across multiple social media platforms.
The system automates the entire workflow — from receiving a video through Telegram to generating captions, processing content with AI, and automatically uploading posts to platforms like YouTube, Instagram, X, and Reddit.
One of the key features was creating a complete review and approval flow directly inside Telegram, allowing users to approve or manage content before publishing without needing separate dashboards or tools.
Key contributions:
• Built an end-to-end automated content pipeline using Python and workflow automation tools
• Integrated Whisper for speech-to-text transcription with OCR fallback support for extracting text from videos when needed
• Used local LLMs with Ollama and Llama 3 to generate captions and social media content automatically
• Automated browser-based uploads across multiple platforms using Playwright
• Developed Telegram-based controls for content review, approval, and publishing workflows
• Designed the system to run fully locally without relying on paid AI APIs
Tech stack:
• Python
• Playwright
• Whisper
• Ollama
• Llama 3
• Telegram Bot API
• OCR Processing
• Browser Automation
• AI Content Pipelines
This project strengthened my experience in AI-powered automation, browser scripting, local AI workflows, and scalable multi-platform content automation systems. Built and implemented automation systems focused on streamlining lead management, customer communication, and sales workflows for businesses using AI and workflow automation tools.
Key contributions:
• Designed and automated complete lead pipelines using n8n workflows
• Integrated Meta Ads lead data into centralized systems for lead tracking, organization, and follow-up automation
• Built AI-powered WhatsApp assistants capable of handling instant customer responses, answering common questions, and maintaining natural conversations
• Developed discovery call assistants to qualify leads, collect customer information, and reduce manual pre-sales work before human sales calls
• Automated repetitive operational tasks across lead handling, messaging, notifications, and follow-up processes
• Integrated APIs and messaging platforms to create seamless communication flows between customers and internal systems
• Improved response times and reduced delays in customer communication through automated workflows and AI-assisted interactions
Tech stack:
• n8n
• WhatsApp Business API
• Meta Ads Integration
• Python
• REST APIs
• AI Assistants / Chatbots
• Workflow Automation Systems
This work focused on helping businesses reduce manual effort, organize lead data more effectively, and create faster, more scalable customer communication systems.