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Built a multi-account Reddit DM bot that scrapes posts across hundreds of subreddits, classifies them by purchase intent using regex scoring, and sends targeted outreach automatically. Running in production on a VPS via PM2.
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AI Lead Qualification & Appointment Automation System
AI Lead Conversion Platform — Telegram, CRM & Automated Scheduling
Designed and developed an AI-powered lead conversion system that handles incoming Telegram conversations from first contact to qualification, CRM synchronization, and appointment booking.
The AI works with conversation history, lead profile data, unanswered questions, current funnel stage, available actions, and verified CRM data to determine the next appropriate step and generate structured responses.
The system automatically creates and updates leads in the CRM, manages qualification stages, books meetings, generates Yandex Telemost links, sends reminders, handles rescheduling, and escalates exceptional cases to a human manager.
The architecture includes dialogue state management, message deduplication and batching, PostgreSQL persistence, concurrency protection, validation before actions are executed, and safeguards against sending unverified or prohibited information.
This is not just an AI chatbot — it is an automated sales workflow that connects Telegram, AI, CRM, scheduling, and human escalation into one controlled process.
AI makes decisions within controlled business rules instead of operating as an unrestricted chatbot.
The concurrency safeguards and validation-before-actions detail is a strong distinction here—booking systems usually fail at the edges, not in the happy path. I’d expose a compact lead state to the operator (stage, next action, last unanswered question) so a human can resume...
🚀 RestoBarApp — Cloud POS & Multi-Tenant Hospitality Management SaaS
Architected and deployed a full production B2B SaaS platform for restaurants, bars, and hospitality businesses with active daily operations and paying subscribers.
Key Engineering & Product Highlights:
• Integrated AI Operations Assistant: In-app conversational assistant powered by Google Gemini API, allowing restaurant managers to query sales velocity, stock anomalies, and daily operational metrics in real-time.
• Granular Inventory Engine: Real-time ingredient tracking down to the gram/milliliter linked directly to recipe consumption upon checkout.
• Real-Time Kitchen Sync: Bi-directional WebSocket events keeping order queues synchronized across multiple kitchen stations with zero page reloads.
• Multi-Branch & Multi-Tenant: Robust tenant data isolation, custom role-based permissions (Cashier, Waiter, Kitchen, Admin), and multi-location management.
• Automated Invoicing & Thermal Printing: Seamless thermal POS receipt generation and automated billing lifecycle management.
🛠 Tech Stack:
Node.js • Express • MongoDB • Real-time WebSockets • Google Gemini API • TailwindCSS • Google Cloud Platform (GCP)
🔗 Live Platform: https://app.restobarapp.com
saasnodejsfullstackFull Stack DevelopmentBackend DevelopmentSoftware ArchitectureGoogle Cloud PlatformMongoDBNode.js
Great work 👍🏻
A demo video showing how the Synapse AI system solves the #1 problem in real estate lead generation: late-night leads going cold. When a lead messages at 11:47 PM, the AI Agent responds in 60 seconds — qualifying the lead, sending automated multi-day follow-ups, and booking the appointment directly on the calendar. Industry average response time is 8+ hours; this system responds in 60 seconds.
Speed-to-lead matters most when the first response tees up the next human action, not just when it is fast. I’d keep the first pass to one qualifying question at a time, make the follow-up cadence explicit, and route high-intent replies to a person with the transcript attached....