This is exactly the kind of partnership I’m looking for too.
I work on n8n + LLM agent deployments — designing systems that actually execute tasks in business operations, not just trigger notifications. I’m comfortable at the architecture stage: auditing the client’s processes, mapping where automation creates real leverage, then building production-grade workflows that can be handed off.
A few things I bring to this kind of collaboration:
- End-to-end workflow design (not just “connect these two apps”)
- LLM integration patterns: RAG, function calling, multi-agent orchestration
- Clean, documented builds that other people can maintain
Long-term collaboration with room to grow is exactly the right format for this kind of work. Happy to get on a call and understand how you approach client projects. What does your typical engagement look like?
Hi,
I’ve read through your brief and this aligns closely with what I’ve been building. The distinction you’re making between automation and intelligent execution resonates, I’ve spent the last year moving beyond simple workflow automation into systems that actually reason about data and make decisions. Your emphasis on architecture stage involvement and per-client context profiles is exactly the kind of work I want to focus on.
My most directly relevant project is a lead qualification chatbot I built using n8n and Claude, which sits somewhere between your problem space and mine. It ingests prospect data from multiple sources, maintains structured context about each lead, constructs dynamic prompts based on real-time information, and returns consistent JSON outputs for downstream record creation. I’ve also shipped an SMS outreach pipeline and call transcription workflow that required complex multi-step orchestration and webhook triggers. The work taught me how to think about error handling and modular architecture at scale, and I’ve worked extensively with OAuth 2.0 credential management across platforms.
I’m based in New Zealand and prefer working with AU/NZ/UK clients, so the timezone alignment is useful. I’d like to move this forward quickly. I can put together a short Loom walkthrough of one of my production systems to give you a concrete sense of my technical approach.
Looking forward to talking.
Two production systems running right now that match what you described:
AI Voice Receptionist for Service Businesses | Leon Gael — Case Study — Voice AI with 7 tools calling CRM APIs during live calls. Dynamic architecture, new client = 4 values changed.
AI-Powered Content Platform — 3 Languages, 100% Automated | Leon Gael — Case Study — 13 n8n workflows, 3 languages, multi-platform publishing. Running 24/7 for months.
Self-hosted stack: Docker, Traefik, PostgreSQL, Redis, n8n worker process. 30 years in software, recently managed 23 government systems. Documentation is non-negotiable on every project.
Based in Honduras (UTC-6). Reunión de 15 min | Jacobo Prudot | Cal.com