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AI Telegram Sales Assistant with n8n & OpenAI
Built an AI-powered Telegram Sales Assistant in n8n using OpenAI, conversation memory, Google Calendar, and Gmail. The workflow receives incoming Telegram messages, answers questions, qualifies leads, handles objections, books meetings automatically, sends confirmation emails, and replies directly inside Telegram. This created a faster, more consistent sales process and helped capture leads even outside business hours.
Key points
Telegram lead-response automation
OpenAI-powered AI Agent
Conversation memory
Lead qualification and objection handling
Google Calendar booking
Gmail meeting confirmations
Automated Telegram replies
Faster response time and after-hours lead capture
The network for creativity
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It shows that you don’t care enough for your users.
Introducing Assistia, a template for AI customer service automation platforms.
Designed specifically for SaaS companies.
It’ll reduce response times and cut support costs by up to 70%.
With its visual storytelling and social proof sections, strategic CTAs, and mobile-first design,
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Check the comments for the links.
A client asked for a booking form.
I built them a calendar instead.
The original ask was simple: a contact form on the landing page so clients could "request an appointment."
But before I touched anything, I looked at how the salon actually runs — services split across stylists, different durations per treatment, staff juggling messages all day just to confirm who's free when.
A form would've just moved the back-and-forth online. It wouldn't have solved anything.
So instead I built a real booking calendar — live availability per stylist, per service, right on the landing page.
No more "let me check and get back to you."
Clients see an open slot, they book it, done.
That one shift saves the salon close to an hour a day that used to go into manually confirming appointments.
This is the part of the job that matters most to me — not just shipping what's asked, but understanding the business well enough to know what's actually going to help it.
Here's the before vs. after.
Which one would make you want to book?
Business Workflow AutomationFramer Website DesignWeb DesignFramerautomationsolutionswebdesignworkflowautomation
I’m currently building a RAG system for an e-commerce company, basically giving an AI assistant access to the company’s own knowledge and product information so it can give useful, context-aware responses instead of just generating random answers.
The interesting part isn’t just connecting an LLM.
It’s making sure the AI can:
→ Find the right information
→ Understand the user’s question
→ Retrieve relevant context
→ Give an accurate response
→ Actually be useful in a real business workflow
Still working on it, but I’m excited about where it’s going.
This is the kind of AI automation I enjoy building, systems that solve actual business problems, not just AI demos.
Building something similar? Let’s talk.
One thing that will save you a lot of time: build a small evaluation set early — 50–100 real questions with the document or product that should be retrieved for each. Before tuning prompts, measure retrieval quality (does the right doc surface in the top 3?) with it. Chunk size...
