Joshua Afolabi
My skill set combines disciplined analytical thinking
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:Finding the right job or candidate manually takes hundreds of hours. To solve this, I engineered a fully autonomous job-hunting engine using n8n, custom API integrations, and Large Language Models (LLMs).
This workflow acts as a 24/7 AI Recruiter. It continuously pulls live job postings from 4 different data sources, filters out the noise, and uses an AI Agent to read the job descriptions and compare them against a specific CV profile.
TECHNICAL CHALLENGES SOLVED
• Multi-Source Aggregation: Integrated 4 separate HTTP data streams and normalized the messy JSON data into a single, clean pipeline using custom JavaScript nodes.
• AI Decision Making: Connected OpenRouter & Ollama LLMs directly into the flow. The AI acts as the "Brain," reading complex job requirements and outputting structured JSON decisions (Match / No Match).
• Resilient Error Handling: Built robust error-catching logic that sends immediate Telegram alerts if any API endpoint fails, ensuring the system never fails silently.
• High-Volume Processing: Utilized Batch/Loop nodes to process hundreds of job postings per minute without hitting API rate limits.
RESULTS & BUSINESS VALUE
✓ Replaced 20+ hours a week of manual job searching and filtering.
✓ Achieved near-instant notification of new, highly-relevant job postings.
✓ Built a scalable architecture that can easily be adapted for real estate, lead generation, or news aggregation.
TECH STACK
n8n • JavaScript • REST APIs • LLMs (OpenRouter/Ollama) • Telegram Bot API • Webhooks • Prompt Engineering
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Building a Portfolio That Actually Converts. 🚀
I just wrapped up the portfolio build for favs._shot, a photography brand focused on raw emotion and bold, editorial imagery.
The challenge? They needed a way to streamline their chaotic booking process and stop losing clients in their DMs.
The result is a custom-built, responsive website that prioritizes both aesthetics and lead generation. The dark, minimalist design keeps the focus entirely on the art, while the integrated, frictionless contact system turns casual browsers into booked sessions directly from the site. A perfect blend of form and function.
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Manufacturing facility managers were flying blind, relying on delayed reports and disconnected spreadsheets to monitor multi-line production status. A modern industrial operation needed a central nervous system. I designed and developed FABRIX AI — a high-performance, real-time command center that aggregates data across active production lines and delivers instant visibility into yield, OEE (Overall Equipment Effectiveness), and maintenance alerts.
The Challenge
Industrial environments generate massive amounts of data, but it's often siloed or presented in outdated, hard-to-read interfaces. The core challenge was twofold:
Data Aggregation: We needed to ingest live statuses, targets, and outputs from multiple concurrent production lines without latency.
Cognitive Load: Operators on the factory floor needed a UI that instantly communicated critical alerts (like yield drops or material shortages) without requiring them to dig through menus. The interface had to be deeply legible in low-light industrial environments while looking like a premium, modern SaaS product.
he FABRIX AI dashboard transformed raw factory data into an actionable, real-time narrative.
Facility managers now have a single pane of glass showing global OEE, total output, and granular line-by-line efficiency.
The high-contrast alert system dramatically reduces response times to yield drops and maintenance bottlenecks.
The fully responsive, single-page application structure allows the dashboard to be displayed on large factory floor monitors or accessed remotely by shift supervisors without losing visual hierarchy.
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📌 Project Title
Multilingual AI Customer Support Bot for Telegram
🎯 Project Overview
I developed a fully autonomous, AI-powered customer service Telegram bot designed to handle customer inquiries 24/7. Built for a client in the cryptocurrency space, this bot acts as a first line of defense, automatically resolving common user issues, collecting support tickets, and routing complex problems to human admins.
💡 The Problem
The client was overwhelmed with customer support requests on Telegram coming from users all over the world. They were spending hours manually answering repetitive questions and struggling to communicate with non-English speaking users.
🚀 The Solution & Features
I built a custom Python-based Telegram bot with the following advanced features:
🤖 Smart AI Matching: Uses PyTorch and a HuggingFace NLP model to actually understand what the customer is asking, rather than relying on strict, dumb keywords.
🌍 Auto-Translation in 7 Languages: Integrates real-time translation. If a user speaks Spanish or Chinese, the bot automatically detects it, talks to them in their native language, but translates the collected ticket into English for the admin!
🔄 Seamless Live-Chat Handoff: If the AI can't solve the issue, it seamlessly connects the user to a human admin for a live 1-on-1 chat directly through the bot.
💻 'One-Click' Auto-Installer: I designed a custom PowerShell installer so the non-technical client could set up and host the bot on their own laptop with a single double-click.
🛠️ Tools & Technologies Used
Python (Core logic and flow engine)
Telegram Bot API (User interface and messaging)
PyTorch & HuggingFace (Machine learning & Natural Language Processing)
deep-translator (Real-time multilingual support)
📈 The Impact
The bot successfully automated the client's tier-1 support, instantly answering FAQs and organizing complex issues into neat, translated tickets for the admin. This saved the client dozens of hours a week and provided instant, 24/7 support to their global user base.
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