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The 3-Second Sales Rep: Autonomous Real Estate Lead Routing (n8n + AI)
Speed is everything.
If a prospect fills out a form on your website and you don't reply within 5 minutes, they are already calling your competitor. The problem? Real estate agents are always driving, on site, or in meetings. They don't have time to watch their email inbox 24/7.
The Problem:
A client was spending thousands on Facebook and website ads, but their conversion rate was terrible. Leads were sitting in an inbox for 3 to 4 hours before a human finally manually copied the data into a CRM and sent a generic "Hi, how can I help you?" text message. By then, the lead was cold.
The Solution:
I completely removed the human bottleneck. Instead of a messy Zapier flow, I engineered a highly stable, autonomous "Digital Sales Rep" using n8n and Agentic AI.
Here is how the digital infrastructure works in real-time:
The Catch: A custom webhook instantly catches the raw lead data the millisecond a form is submitted.
The Brain: The data is securely passed to Google Gemini 1.5 Pro. I prompted the AI to "read" the prospect's message and categorize their intent (e.g., Are they a First-Time Buyer? A Commercial Investor? A Seller?). It also extracts their budget.
The Guardrails: I wrote a custom Javascript/Python node to enforce strict JSON formatting. This stops the AI from hallucinating and ensures the data perfectly matches the CRM schema.
The Action: The system instantly drops the clean data into the CRM, sends a loud "Hot Lead" alert to the sales team's Slack channel, and fires off a highly personalized SMS (via Twilio) to the prospect based on their exact budget and intent.
The Impact:
We took the lead response time from 3 hours to under 3 seconds.
The agency stopped losing leads to competitors, completely eliminated manual data entry, and sales reps walked into work with a pipeline full of warm, engaged conversations already happening on their phones.
Are you tired of losing leads to slow, manual processes? I build digital infrastructure that works while you sleep. Send me an inquiry and let's whiteboard your new system.
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AgentFlow10 — AI Agent & Automation Platform
Lead Engineer · Self-hosted AI agent platform with a visual workflow builder
The problem
Automation tools are built for businesses that already have a card on file, reliable bandwidth, and a Slack workspace. That leaves most of the world out. In markets where WhatsApp is the customer channel and mobile money is the payment rail, the standard automation stack either doesn't connect or is priced in currencies that make it a non-starter.
There was a second problem. Every serious automation platform is someone else's cloud. If your data is sensitive, or your compliance rules keep it in-country, or you just don't want to hand your customer records to a vendor, your options run out fast.
What I built
AgentFlow10 is an AI agent and automation platform you can run on your own infrastructure. A visual builder lets you compose agents and multi-step workflows without writing code, connect them to the tools you already use, and deploy them where your data lives.
The design goal was to make AI agents something a small team can actually operate — not a research project requiring an ML engineer on staff.
What I did
I built and run it end to end: product direction, backend architecture, LLM orchestration, integration layer, the workflow engine, frontend, brand system, and go-to-market. Everything from the database schema to the landing page copy.
Notable pieces of engineering:
A workflow execution engine that handles branching, retries, and failure states — because an agent that dies silently mid-run is worse than no agent
LLM orchestration with prompt management and output validation, so results are structured and usable rather than free text
A self-hosting path that a non-specialist can actually deploy
Integration architecture designed for channels that matter outside Silicon Valley, including WhatsApp and mobile money flows
Why it matters for clients
This is the project I point to when someone asks whether I can build AI systems rather than just call an API. Running a platform means I've dealt with the parts that break in production — cost control, rate limits, non-deterministic model output, failure recovery. That experience is what I bring to client work.
Built with: Python, TypeScript, React, Next.js, Node.js, PostgreSQL, LLM APIs, Docker
Klaviyo Email Flow Setup & Automation
I designed and structured automated Klaviyo flows for ecommerce brands to engage customers at key moments throughout the buying journey.
The flows are built around customer behavior, with strategic timing, segmentation, messaging, and conversion-focused email design.
Flows include:
Welcome Series
Abandoned Cart
Browse Abandonment
Post-Purchase
Winback
Customer Review
Cross-Sell & Upsell
The goal is simple: deliver the right message at the right time, recover missed opportunities, and create more repeat purchases through automation.
Built a complete in-house telephony solution for Edwin INC as a full replacement for Teleforce. Developed using Node.js, Express, and Plivo features include a 14-agent simultaneous ring system, Plivo Browser SDK integration, SIP endpoints, Zoho CRM integration, call recording, voicemail, and real-time call routing dashboard. Hosted on Hostinger with Supabase (PostgreSQL) database. This tool eliminated the dependency on third-party calling software and saved significant operational costs for the company.
Impressive project! Building a complete in-house telephony platform with CRM integration and real-time call routing is a strong example of practical automation and cost optimization. 🚀