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Built a local workflow tool that turns exported order and after-sales spreadsheets from multiple e-commerce platforms into a structured daily operations report.
The tool supports batch importing Excel files, validates supported export formats, combines order and refund data, and generates a clean Excel summary with per-platform totals and an overall daily total. All processing is done locally on the device.
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
A live interactive Sales Analytics Dashboard built in Power BI Desktop using the Superstore retail dataset.
I designed and developed the CodeQubic website for a client, creating a modern, responsive, and conversion-focused web experience that represents their brand and services.
Built with Next.js, React, TypeScript, and modern UI practices, the project focuses on clean visual design, smooth interactions, responsive layouts, and a scalable frontend architecture.
The goal was to give the client a professional digital presence that clearly communicates what they offer while providing a fast and engaging experience across devices.
