Beauty salon · Toronto
13 workflows in production
Salon operations, running end to end
The problemBookings, client notes, reviews and follow-ups lived in different places. Nothing talked to anything, so the work fell on whoever remembered it that day.
What I builtA connected system rather than a set of scripts: customer sync from the booking platform, a daily pull of client notes, outbound message campaigns with cooldown rules so nobody gets contacted twice, review scanning with drafted replies, a bi-weekly staff report, plus a pipeline monitor and error handler that page me before the owner notices anything.
+73%review volume
26 / 170lapsed clients recovered, campaign still running
n8n · Square API · Google Business Profile · Sheets · Telegram alerting · scheduled orchestration
AI pipeline
Content pipeline from a single voice note
The problemPublishing one post meant transcribing a recording, writing copy, finding an image, posting it, then logging it. Five tools, every time.
What I builtA pipeline triggered from a chat message. It takes text or voice, transcribes the audio, drafts the post through an LLM agent with a tuned prompt, publishes it with a generated image, then extracts metadata into a spreadsheet and calendar. Access control, command routing and conversation memory included.
1 messagefrom voice note to published, logged post
n8n · Whisper · LLM agent · image generation · Sheets & Calendar API · Telegram Bot API
Content system3 workflows, always on
LinkedIn publishing with its own feedback loop
The problemPosting consistently is a scheduling problem. Knowing whether any of it worked is a different problem, and the analytics only exist as screenshots.
What I builtTwo scheduled publishing pipelines that research, draft and post on their own cadence — plus a stats workflow that reads screenshots of the platform's analytics through a vision model, writes the numbers to a sheet, and sends a weekly performance summary.
Weeklyperformance report, assembled without manual entry
n8n · Claude · vision model · Google Sheets · Telegram · cron orchestration
Voice agent
Booking agent on voice and chat
The problemA service business lost bookings during its busiest hours for the dumbest reason: nobody was free to answer the phone.
What I builtA voice agent and chat interface sharing one backend, wired to the booking system through MCP. It handles hours, availability and rescheduling on its own, and hands anything unusual to a person with the context already gathered.
Unattendedroutine bookings handled with no staff involved
n8n · voice AI agent · MCP integration · booking API · chat memory
Hostel · Poland
Taking the phone queue off the front desk
The problemGuests could not get through by phone, so the complaints landed in Google reviews instead. The rating sat at 3.7.
What I builtWe traced what was actually driving the bad reviews, then put a voice agent in front of the phone line to answer the questions that made up most of the call volume. Over half of callers got what they needed without ever reaching the desk.
3.7 → 4.1Google rating · ~24% more footfall
n8n · voice AI agent · telephony integration
43-person team
Email campaign production, rebuilt
The problemEvery campaign was assembled by hand: copy into templates, templates into the sender, lists rebuilt from scratch each time.
What I builtTemplated production that took the manual assembly out of the loop, so the team spent its time deciding what to send rather than how to send it.
~170hremoved per month · 30% faster cycle
n8n · templated HTML · marketing platform integration
RAG
A knowledge base of my own workflows
The problemEvery new automation started from a blank canvas, even when a near-identical one had been built months earlier and forgotten.
What I builtA searchable database of existing workflows stored as vector embeddings, queried in plain language by an agent that returns the closest working pattern and explains how to adapt it.
Reusepatterns retrieved instead of rebuilt
n8n · Supabase vector store · embeddings · RAG · AI agent
Side project
A YouTube channel that runs without me
The problemI wanted to find out how far an unattended content pipeline could actually go before a human has to step in.
What I builtA daily pipeline that writes the script, generates voiceover and visuals, assembles the video and publishes it on schedule — with a separate push workflow for uploads and a pull for analytics.
Dailypublishing on a schedule, hands off
n8n · Claude · ElevenLabs · image generation · YouTube Data API · VPS