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Automated Lead Management System — built with n8n to capture incoming leads, automatically store them in Google Sheets, and instantly notify the sales team on Telegram. Faster response, less manual work, and no missed leads.
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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Project title: AI Voice & Text Personal Assistant for Slack
Project description:
Built a conversational AI assistant in n8n that lives inside Slack and handles both voice and text messages, giving users a personal assistant they can talk to naturally, without switching apps or typing long commands.
The problem: The client wanted a way for their team to quickly get answers or delegate tasks through Slack, including by voice, without building a separate app or bot from scratch, and needed the assistant to hold context across a conversation rather than treating every message as a one-off.
What I built:
Message filtering: Every incoming Slack message is automatically checked to filter out bot-generated messages, so the assistant only responds to real human input.
Voice and text handling: The system detects whether the incoming message is a voice note or plain text. Voice messages are automatically downloaded and transcribed into text using an audio transcription model, while text messages pass straight through, so both input types end up in the same format for processing.
Conversational AI agent with memory: The transcribed or typed message is sent to a personal AI agent (built on Groq) that generates a response. The agent uses a memory module to retain context across the conversation, so it can handle follow-up questions naturally rather than starting fresh every time.
Instant reply in Slack: Once the agent generates a response, it's posted straight back into the Slack channel, so the interaction feels like a live conversation.
Outcome: The client's team now has a Slack-native assistant that understands both typed and spoken messages, remembers conversation context, and responds instantly, no separate app, no manual transcription, no lost context between messages.
This is good
Just wrapped up building flux/, an interactive UI with real-time WebGL rendering, custom GLSL shaders, and scroll-driven animation, built entirely from scratch with vanilla JS, what do you think?
It's been a super fun shift for me, most of my background is Python automation, AI integration, and data pipelines, but diving into frontend/UI work like this has been genuinely rewarding.
Link's in my portfolio if you want to see it in action. Always open to talk automation, AI integration, or interactive web work.
The vanilla JS route is the part I would defend - straight to GLSL instead of inheriting a scene graph you never needed. The one that caught me on scroll-driven work was portrait: visible width is 2*z*tan(fov/2)*aspect, so at 0.75 aspect you see less than half of what you...
I built an AI-powered Telegram assistant that handles incoming messages, understands requests, and responds automatically.
Using n8n, Google Gemini, and memory, the workflow helps reduce repetitive manual responses and keeps communication moving without constant intervention.
