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Built an end-to-end AI Customer Operations System using n8n, OpenAI, HubSpot, Gmail, Slack, and Google Sheets. It automatically classifies incoming emails, routes sales and support requests, scores lead priority, updates CRM records, alerts teams, drafts replies, and escalates sensitive cases for human review.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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My core stack is less "generate pretty pictures" and more "build the pipeline that does the thinking":
n8n — the glue. Great for orchestrating multi-step agent workflows and connecting APIs without writing a service from scratch. Weakness: gets messy fast on complex branching logic, and debugging a broken node chain eats time.
RAG (usually with a vector DB + LangChain-style retrieval) — lets me ground LLM output in actual client data instead of hallucinated generalities. Strength: dramatically improves accuracy for domain-specific asks. Weakness: chunking/retrieval quality is finicky, and a bad embedding setup silently tanks results without throwing an error.
Claude/GPT for reasoning + code — my default for anything needing judgment: analysis writeups, SQL/Python generation, proposal drafting. Strength: fast iteration. Weakness: still needs a human check on numbers — confident-sounding ≠ correct.
Power BI / Tableau — where the AI output actually becomes something a client trusts. AI can shortcut the analysis, but the dashboard is what gets signed off on.
The honest lesson: the "AI" part is maybe 30% of the workflow. The rest is validation, data plumbing, and making the output legible to a non-technical stakeholder.
Silent failures are what I watch closest. I treat an answer as untrusted unless I can show exactly which source text the model read, because fluent output can hide a bad match.
Designed a modern AI Voice SaaS Dashboard.
Clean and intelligent UI with real-time voice analytics, call insights, conversation tracking, AI-powered features, and performance metrics for smarter customer communication.
Amazing work
AI News Digest
I built an automated AI News Digest with n8n that collects the latest AI & automation news from RSS sources, selects the most relevant items, summarizes them using Groq AI, and delivers a structured daily digest directly to Telegram.
The workflow runs automatically every day, eliminating the need to manually check multiple sources.
Built with n8n, RSS, Groq API, Telegram API, and JavaScript.
A simple example of how AI automation can turn information overload into a useful daily workflow.
