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Galley CRM: a sales CRM for restaurant-focused businesses with lead scoring, pipeline stages and a native automation engine (Postgres triggers plus a pg_cron worker). On top of it I built n8n workflows with an AI agent that qualifies leads over WhatsApp and Instagram using CRM tools, and a daily follow-up flow that finds stalled leads, drafts re-engagement messages and decays their score. Built and tested on a dedicated demo instance.
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Experimented a bit today with Krea and image generation for a case study I’m putting together around AI EarPods connected to OpenAI.
The focus has been on creating fashion-forward product imagery and art directing a world that feels specific to the identity, rather than just generating nice-looking AI images.
The trickiest part has been product consistency. Especially getting the EarPods to actually sit snug in the ear. If you’ve worked through this process, you probably know the struggle 😅
Simply telling AI to “make it fit more snug or in the ear” doesn’t always work. It loves to reinterpret the product every time.
Still experimenting, but getting closer. If anyone has found a good workflow for keeping products consistent across AI-generated shoots, I’d love to hear it!
TOP!
CRM complexity grows quickly when systems, data and processes stop working together.
ChargedEV partnered with me to simplify and modernise its CRM ecosystem while supporting the company’s continued growth.
The business was operating across multiple HubSpot portals and several disconnected systems, which had created duplicate processes, fragmented customer data and unnecessary manual work.
My role was to help turn that environment into a single, scalable CRM platform.
I consolidated two HubSpot portals into one environment, managed the migration from HubSpot Enterprise to Professional, redesigned the CRM architecture, and migrated and validated business-critical data.
From there, I built automated workflows for sales and operational processes, created custom reports and management dashboards, and connected HubSpot with systems including Jira, Confluence, WooCommerce, Aircall, Calendly, Typeform and Companies House.
The engagement ultimately covered 670+ pieces of CRM work, spanning migration, automation, reporting, integrations and ongoing optimisation.
The result was a much more connected CRM ecosystem, with cleaner data, fewer manual processes and a stronger foundation for the business to continue scaling.
Projects like this are a good reminder that CRM transformation isn’t simply about moving data from one system to another. The real value comes from simplifying the architecture and making the different parts of the business work together.
Strong systems thinking here—consolidating the CRM and validating the migration, rather than just moving data, is what makes the work genuinely scalable.
🛠️ Show & Tell: AI Voice Receptionist — Retell AI + n8n + Google Sheets + Retool
Hey Contra community 👋
Just wrapped a full AI voice receptionist build for a home services client and wanted to share what went into it.
What it does:
Answers inbound calls 24/7 using Retell AI
Runs 3 real-time checks via n8n: service area · slot availability · customer lookup
Books the appointment live on the call — no double-booking
Logs to Google Sheets and fires a confirmation email automatically
Full Retool command center for the client to manage everything
The tricky part:
Retell AI has a toggle called "Payload: args only" — when enabled, it strips the parent wrapper from the webhook payload. Took a solid debug session to figure out why n8n kept returning empty data. Once I caught it and rebuilt the payload mapping, everything worked end to end.
Stack: Retell AI · n8n · Google Sheets · Retool MCP
Happy to answer questions on any part of the build — webhooks, n8n sub-workflow structure, Retool dashboard setup, whatever.
If you're a builder who gets overflow work in voice AI or home services automation, let's connect 🤝
Nice systems thinking in this build—the handoff between voice intake, availability checks, booking, and confirmation is clearly mapped to a real user outcome. The Retool command center also makes the automation legible instead of hiding it behind the scenes.