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Afolabi Samuel's avatar
Afolabi Samuel
Osogbo, Nigeria
AI Developer | Mobile App Developer | Full Stack Engineer
32
Followers
AI Developer | Mobile App Developer | Full Stack Engineer
Cover image for AI Customer Notification & Order
AI Customer Notification & Order Processing System with n8n I developed a complete AI-powered order processing workflow in n8n that automatically receives customer orders through a webhook, validates incoming data, stores the order in Google Sheets, sends confirmation emails, delivers Telegram notifications, and handles follow-up messages without manual intervention. The workflow was designed to eliminate repetitive administrative tasks while ensuring customers receive immediate confirmations and businesses receive real-time notifications. Problem Businesses often spend valuable time manually recording orders, sending emails, updating spreadsheets, and notifying internal teams. This slows operations and increases the risk of human error. Solution I built an automated workflow that: • Receives new orders instantly via Webhook • Validates customer information • Stores order details inside Google Sheets • Sends branded Gmail confirmation emails • Sends instant Telegram notifications • Waits automatically before sending follow-up messages • Reduces manual work and improves customer experience Technologies Used n8n Webhooks Google Sheets API Gmail API Telegram Bot API JSON API Integration Workflow Automation AI Automation Skills AI Automation Workflow Automation API Integration Backend Automation Business Process Automation AI Coding n8n Development No-Code Automation System Integration Tags #AIAutomation #n8n #WorkflowAutomation #APIs #GoogleSheets #TelegramBot #GmailAPI #Webhook #BusinessAutomation #AutomationEngineer #LowCode #BackendAutomation #AICoding #SystemIntegration #Developer🚀 🚀 🚀
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Cover image for AI Customer Support Agent With
AI Customer Support Agent With CRM & WhatsApp Integration I built an AI-powered customer support system that automates conversations across multiple channels while synchronizing customer data with CRM platforms. The AI agent can answer questions, qualify leads, collect customer information, and notify teams in real time. The workflow reduces response times, improves customer engagement, and eliminates repetitive manual tasks. Problems Solved Slow customer response times. Manual lead qualification processes. Poor synchronization between communication channels and CRM systems. Inefficient customer support operations. Solution Built an intelligent AI support agent. Integrated CRM platforms for automated customer management. Automated WhatsApp and Telegram notifications. Implemented webhook-based API integrations. Enabled real-time customer data processing. Technologies Used AI Automation API Integration Webhooks CRM Automation JavaScript n8n Botpress OpenAI API WhatsApp Automation Telegram Bots Skills AI Agent Development Workflow Automation API Integration CRM Automation Backend Development AI Coding Process Automation Tags AI Agent AI Automation CRM Integration Bot Development API Integration WhatsApp Automation Botpress n8n JavaScript Workflow Automation🚀 🚀 :🚀
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Cover image for AI-Powered Order Confirmation & Customer
AI-Powered Order Confirmation & Customer Notification System I developed an intelligent order confirmation system that automatically validates customer orders and delivers real-time notifications across multiple communication channels. The workflow instantly receives customer information through webhooks, processes the submitted data, stores transaction records securely in Google Sheets, sends personalized Gmail confirmations to customers, delivers Telegram notifications to administrators, and automatically schedules follow-up messages using timed delays. The system was designed to eliminate manual order handling, improve response times, and provide customers with a seamless post-purchase experience. By integrating automated messaging, data management, and delivery tracking, businesses can process orders more efficiently while maintaining professional customer communication. Features Automated order confirmations Real-time customer notifications Google Sheets data storage Gmail email automation Telegram notifications Wait node follow-up messaging Webhook integrations Delivery tracking automation Multi-step workflow processing Scalable API integrations Problem Solved Businesses often spend valuable time manually confirming orders, updating customer records, and sending notifications across different platforms. This creates delays and increases the possibility of human errors. Solution I developed an intelligent workflow that automatically receives customer orders, validates information, sends notifications instantly, manages delivery updates, and provides seamless communication throughout the entire process. Tools Used n8n Gmail API Telegram Bot API Google Sheets API Webhooks Wait Node Automation API Integrations Skills AI Software Development Backend Development Workflow Automation API Integration Business Automation Full Stack Development Data Processing System Design Tags AI Development Software Engineering n8n Workflow Automation API Integration Google Sheets Gmail Automation Telegram API Backend Development🚀 🚀 🚀
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Cover image for AI Multi-Customer Order Processing &
AI Multi-Customer Order Processing & Notification System I designed and developed an intelligent multi-customer order processing system using n8n that automatically handles VIP and regular customer orders through separate processing pipelines. The workflow validates incoming orders, categorizes customers based on predefined conditions, records transaction data into Google Sheets, sends instant Telegram notifications to administrators, delivers personalized Gmail confirmations to customers, and manages fulfillment status updates automatically. The system significantly reduces manual processing time while improving order accuracy and customer experience. VIP customers receive priority handling with customized notifications, while regular customers follow a dedicated processing workflow. Conditional logic, automated branching, and webhook responses ensure seamless communication between all connected services. Features Multi-customer order processing VIP customer priority handling Automated Google Sheets data storage Gmail order confirmation emails Telegram admin notifications Conditional workflow branching Real-time webhook processing Fulfillment status management Automated delivery notifications Scalable API integrations Problem Solved Businesses often waste time manually processing customer orders, sending confirmations, and updating records across multiple platforms. Manual workflows increase processing delays and human errors. Solution I developed an intelligent automated system that instantly processes customer information, prioritizes VIP orders, sends notifications, stores data securely, and improves operational efficiency without requiring manual intervention. Tools Used n8n Gmail API Telegram Bot API Google Sheets API Webhooks Conditional Logic API Integrations Skills AI Software Development Workflow Automation API Integration Backend Development Business Process Automation System Design Data Processing Full Stack Development Tags AI Development n8n API Integration Workflow Automation Google Sheets Backend Development Webhooks Software Engineering Business Automation🚀 🚀 🚀
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JSON PowerDB(1)
Michael Gould's avatar
Michael Gould
proLorton, USA
Workflow automation for forms, CRMs, Zapier, Make, n8n.
New to Contra
Workflow automation for forms, CRMs, Zapier, Make, n8n.
Cover image for Self-initiated internal product. Odds Desk
Self-initiated internal product. Odds Desk uses public data only. It is not client work, a trading tool, or financial advice. I built this because a research brief is only as trustworthy as the source snapshot behind it. Catalog freshness, derived summaries, file identity, and editorial status need to stay consistent across every generated artifact. The workflow synchronizes a public catalog, exports one canonical bundle, generates and validates a summary, regenerates a manifest, checks declared SHA-256 values against disk, and produces a dashboard and Markdown brief from the same saved files. The workflow fails closed. If a required validation fails, the bundle stops, the evidence is preserved, and no buyer-ready issue is produced. The gallery shows a July 30, 2026 snapshot with 675 saved markets, 36 unverified research leads, zero verified cards, and four of four declared hashes matching disk. The state remains RESEARCH_PREVIEW. Best fit: public API ingestion, reproducible research bundles, validation pipelines, provenance checks, fail-closed editorial workflows, and automated briefing systems.
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Cover image for HVAC Lead Handoff Rescue Case Study
HVAC Lead Handoff Rescue Case Study
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Cover image for A self-initiated workflow automation demo
A self-initiated workflow automation demo showing a simple lead handoff: intake, routing, CRM or sheet logging, owner notification, and test-ready review output.
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Cover image for A self-initiated Brief Factory internal
A self-initiated Brief Factory internal system. The gallery shows public post titles only. No names, handles, contact details, or private messages are shown. I built this to make public automation research more consistent. Instead of manually checking communities for scattered requests, the monitor reads selected RSS and Atom feeds, normalizes source URLs, rejects stale or generic items, scores observable workflow pain, deduplicates accepted rows, and records source health. The output is a structured review queue, not permission to contact anyone. The system does not post, bid, message, or send. The gallery shows a dated run from July 30, 2026: seven configured feeds, seven review rows, two HTTP 429 rate limits, zero high-intent rows, and zero external actions authorized. Best fit: public-source monitoring, qualification queues, source-health reporting, research triage, and review-first opportunity workflows.
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JSON PowerDB(1)
Siddiq Tashfeen's avatar
Siddiq Tashfeen
St. John's, Canada
Full-Stack Engineer | AI Automation & Workflow Systems
33
Followers
Full-Stack Engineer | AI Automation & Workflow Systems
Cover image for Built an AI-powered news automation
Built an AI-powered news automation system using n8n and Google Sheets that collects articles, filters data, processes content with AI, and automatically updates structured records for marketing insights and content tracking.
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Cover image for Outbound Lead Generation & Automation
Outbound Lead Generation & Automation System (Email + LinkedIn) I built a complete outbound system to generate and convert high-quality B2B leads using email and LinkedIn automation. The system starts with ICP-based lead sourcing, targeting companies by size, revenue, industry, and C-level roles. Leads are enriched, segmented, and automatically routed into a structured outreach flow. I designed a 6-step email sequence where messaging evolves at each step to increase reply rates. LinkedIn actions are timed between email touches to create a natural multi-channel outreach without overlap. The main challenge was coordinating multiple tools while maintaining deliverability and clean data flow. I solved this by building a centralized automation layer that handles sequencing logic, delays, and real-time updates across systems. A lightweight CRM tracks every lead from first contact to final outcome, including replied, interested, and not interested. This provides clear visibility and allows continuous optimization. The system is structured for scalability and simple handoff, so it can be managed without technical dependency.
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Cover image for Built a feedback and workflow
Built a feedback and workflow management system focused on collecting, organizing, and prioritizing user-driven inputs across multiple channels. The platform provides a structured interface where feedback items move through defined stages, enabling teams to track status, engagement, and impact in a clear and scalable way. On the backend, I designed data models and filtering logic to support advanced querying, segmentation, and lifecycle management of feedback items. Implemented role-based access control and admin-level configurations to manage permissions, visibility, and workflow transitions. This ensures that internal teams can efficiently manage large volumes of data while maintaining consistency and control. On the frontend, I focused on building clean dashboards and interactive views that surface key metrics such as user reach, engagement, and revenue impact. I also implemented public-facing and read-only views, allowing external users to submit feedback and track updates without direct system access. This improves transparency while keeping the system secure and well-structured.
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Cover image for I built a workflow management
I built a workflow management system focused on tracking projects from start to completion with clear visibility and control at every stage. The core of the system is a multi-role dashboard that presents real-time data in a structured way, allowing different users to quickly understand project status, performance metrics, and operational health without digging through raw data. On the backend side, I designed structured data models and lifecycle flows to manage how tasks move through different stages (creation → in-progress → completed). I implemented role-based access control and admin-managed configurations so the system can handle multiple users, permissions, and dynamic updates reliably. The goal was to make the system scalable and maintainable while keeping the logic clean and predictable. For the frontend, I focused on building intuitive dashboards and reporting layers that translate complex data into simple, actionable insights. I also implemented shareable, read-only views so external users can track progress through a secure link without needing full access. This improves transparency while maintaining control over the system, which is critical for B2B workflow tools.
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JSON PowerDB(1)
Shafik Muwanga's avatar
Shafik Muwanga
Huddinge, Sweden
Creative Director who brings brands and stories to life.
$25k+
Earned
1x
Hired
4.8
Rating
2
Followers
Creative Director who brings brands and stories to life.
Cover image for Product Vision and Go-to-Market Strategy for SaaS Platform
Product Vision and Go-to-Market Strategy for SaaS Platform
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Cover image for Brand Identity Refresh for Miljonbemanning AB
Brand Identity Refresh for Miljonbemanning AB
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Cover image for qodra.work
qodra.work
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Edgaras Kamandulis's avatar
Edgaras Kamandulis
Salò, Italy
High-Frequency Decision Architect for Zero-Latency Business
High-Frequency Decision Architect for Zero-Latency Business
Cover image for Huntsman: Real-Time Crypto Data Aggregator Engineered a high...
Huntsman: Real-Time Crypto Data Aggregator Engineered a high-performance asynchronous data aggregator using Python asyncio and ccxt.
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Cover image for This isn't Finance. It's Physics. Markets are fluids. Price ...
This isn't Finance. It's Physics. Markets are fluids. Price is velocity. Crash is turbulence. While you stare at RSI, I am calculating the Laminar Flow. My S.C.A. Protocol applies Navier-Stokes equations to capital. If you understand this graph, you know why we need to talk. ​The Second Quantum Revolution is here.
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Cover image for LIBRARIAN CORE: Architecting Intelligence beyond the "0=0" A...
LIBRARIAN CORE: Architecting Intelligence beyond the "0=0" Axiom Most people use AI to write emails. I built the Librarian to navigate reality. The screenshots below show the result of a single afternoon of intense development. It’s not 'pretty' yet, and it’s not finished—it is raw Backend Logic manifesting as an interface. I spent my time stabilizing the architecture and the core consistency of the system. The Philosophy behind the Code: Everything I build starts with a fundamental pact: 0=0. Absolute coherence. Truth. Input must equal Output. This is the mathematical baseline required to find truth within data. However, the Librarian knows that stasis is death. In his core, 0=0 is a fatal termination error. Why? Because if a system only confirms what it already knows, it isn’t evolving. It is just waiting to become dust. 🌌
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Cover image for Evolutionary Parameter Tuning Engine (Python) To solve the p...
Evolutionary Parameter Tuning Engine (Python) To solve the problem of market stagnation in HFT (High-Frequency Trading), I architected a Genetic Algorithm that evolves the bot's configuration in real-time. Instead of static settings, the system spawns a population of 40 different trading 'personalities'. It forces them to compete in a stochastic simulation based on recent market data. The Process: Selection: The top 10% performing configurations are isolated. Crossover: Their traits (RSI thresholds, Risk multipliers) are spliced together. Mutation: Random variations are introduced to discover new local optima. As shown in the terminal log, the system automatically evolved a strategy that increased efficiency from 263.3 to 492.8 in 15 generations, injecting a high-frequency aggressive configuration into the live bot.
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