Custom AI applications
Dashboards and internal tools that give you visibility into what your AI systems are doing and how they're performing.
About
AI systems that drive real business outcomes
I build production-ready AI products and automation workflows with a practical focus on speed, reliability, and measurable ROI.
What I do
I help founders and teams move from AI ideas to real systems: assistants that answer from your knowledge base, voice agents that qualify leads, and workflow automations that remove repetitive operations.
- - Custom AI applications with secure integrations and dashboards.
- - n8n AI agent workflows with monitoring and failure handling.
- - RAG assistants and chatbots for support and internal operations.
- - Voice AI experiences for sales, support, and lead qualification.
Quick stats
4.8/5 ⭐
Average Rating (100+ Deployments)
Top Rated 🏆
Upwork & Level 2 on Fiverr
100% 🚀
Job Success Score
My journey in agentic AI
My work sits at the intersection of AI engineering and operations. I care less about demos and more about AI systems that run every day without you thinking about them.
Over the past several years, I've helped teams ship RAG assistants, AI voice experiences, and n8n workflows that quietly take over repetitive tasks. Each project reinforces the same idea: good AI feels boringly reliable to the people who depend on it.
That is why I lean into production constraints early — data privacy, monitoring, failure paths, and measurable KPIs — instead of treating them as afterthoughts.
Areas of expertise
Specialised skills that help move projects from proof-of-concept to stable production systems.
n8n AI agent workflows
Designing resilient flows that connect CRMs, helpdesks, and internal tools with clear error handling and observability.
Agentic AI & RAG systems
Assistants that retrieve from your knowledge base, reason over context, and act in constrained ways that are safe for your business.
Conversational & voice experiences
Chat and voice agents for support and sales that integrate with your existing channels and play nicely with human teams.
How I work
My approach is intentionally hands-on and system-oriented: define outcomes first, map real constraints, then ship an MVP quickly with observability built in. From there, we iterate toward scale.