Real workflow automation for business scaling goes beyond basic software tools. Businesses grow faster when repetitive tasks, manual data entry, and disconnected systems are replaced with automated workflows.
As a certified AI engineer, I design no-code automation pipelines that streamline operations and remove workflow bottlenecks. These systems connect platforms, automate decisions, and ensure data moves instantly between tools.
In practice, this means building intelligent automations such as AI-powered lead qualification systems and fully automated WordPress publishing pipelines using Make and Google Gemini.
Who I Help
Who I build enterprise-grade automations for
Marketing Agencies
SaaS Companies
B2B Service Businesses
E-Commerce Brands
Coaches & Consultants
Recruitment Agencies
Below, you’ll find the technical breakdown of real production systems I’ve built. Each example highlights the automation logic, API structure, and the measurable hours saved through efficient workflow design.
01. Autonomous SEO Content Engine (Make.com + WordPress)
The Challenge
Manual SEO production is slow and unscalable, typically costing 4+ hours per high-quality expert article.
The Logic
Engineered a multi-stage pipeline using Null-Status Filters and JSON formatting to automate research, writing, and publishing.
02. AI Lead Intelligence Automation (n8n + OpenAI +GHL)
The Challenge
Sales teams waste 10-15 minutes per lead on manual research, leading to slow response times and missed deal context.
The Logic
Built a secure n8n pipeline via Cloudflare Tunnels to intercept GHL webhooks and perform real-time business intelligence analysis.
03. Automated Lead Capture Pipeline (Zapier + Gmail + GoogleSheet)
The Challenge
A marketing agency was losing efficiency to manual data entry, causing slow lead response times.
The Logic
Built an API-driven payload bridge to organize inquiries into a master database automatically.
04. Autonomous AI Outreach Engine (Apollo.io + Google Sheets + Make.com + Google Gemini AI + Gmail)
The Challenge
B2B outreach typically fails due to slow manual research or domain-burning generic templates that offer zero personalization.
The Logic
Built a zero-touch orchestration using Apollo.io for data, Gemini for real-time website analysis, and Make.com for agentic execution.
05. Automated AI Lead Qualification
The Challenge
Growing businesses lose high-ticket deals to manual data entry bottlenecks and delayed lead responses.
The Logic
Engineered an API pipeline that uses LLMs to score leads (Hot/Warm/Cold) and parse data into JSON.
06. Automated AI Auto-Blogger Engine
The Objective
Eliminate manual research and drafting cycles by transforming RSS triggers into high-quality WordPress drafts.
The Solution
A resilient multi-node Make.com architecture using advanced prompt engineering to ensure SEO-ready HTML output.
07. AI Ad Creation Tool (URL-to-Ad Video)
The Challenge
Traditional cinematic ad production for high-ticket services takes weeks and thousands of dollars per iteration.
The Logic
Architected a zero-touch engine using Gemini 2.5 Flash for “Brand DNA” extraction and MoviePy for headless vertical video assembly.
08. AI Voice Assistant for Plumbers
The Challenge
Standard voice bots hallucinate prices when speech-to-text engines mishear messy audio from frantic callers during after-hours emergencies.
The Logic
Engineered a bridge using Vapi tool calls and Make.com data-normalization functions, locking the agent down to a strict, case-insensitive pricing matrix.
How a Project Works — From First Call to Live Automation
Discovery Call
Free, 20 MinsYou tell me what your team does manually today. I ask questions, identify the bottleneck, and tell you whether automation can solve it — and roughly what it would take. No cost, no commitment.
Scope & Proposal
1–2 DaysI map out the full automation architecture — which tools connect, what triggers what, where the AI logic lives, and what the output looks like. You get a written proposal with a timeline and fixed price before any work starts.
Build & Test
Active BuildI build the system, run it through real data, handle edge cases and errors, and document everything. You get progress updates throughout. Simple builds take 2–4 days. Complex AI systems take 2–4 weeks.
Handoff & Support
14-Day GuaranteeI walk you through the live system, hand over full documentation, and give you 14 days of free support for any fixes or adjustments. Most clients are running autonomously within a week of handoff.
