The network for creativity
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Creatives on Contra have earned over $150M and we are just getting started
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AI-Powered RAG Knowledge Base & Chat Assistant
Built an intelligent n8n workflow that automatically ingests documents into a Qdrant Vector Database using Ollama embeddings, creating a searchable knowledge base. When users send a message, an AI agent retrieves the most relevant information through Retrieval-Augmented Generation (RAG), maintains conversation context with memory, and delivers accurate, context-aware responses. The solution enables fast, private, and scalable AI-powered customer support and internal knowledge retrieval without relying on cloud-based LLM infrastructure.
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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I've been steadily building a system to help me service my clients better and make sure nothing falls through the cracks.
The biggest differentiator? It holds full context about who I am and what I do best. So when I open a terminal, find a project on Contra, and start outreach, the system already knows my voice, my work history, and what makes a good fit. I still make sure every proposal is on point before shipping, but the scaffolding is already there.
Beyond initial setup, I keep it lean: faster models for quick pulls (Haiku), smarter ones (Sonnet) for judgment calls. Built on top of Nate Herk's AIS-OS template and Andrej Karpathy's LLM Wiki pattern, two frameworks that help LLMs hold context across sessions without losing the thread.
Today I asked Claude (and Gamma) to map out what we've built over about a week. See what it generated below.
Most of the connections to @Contra HQ and other tools run via MCP, basically live data pipes that let the system read my calendar, inbox, meetings, and revenue without me having to copy-paste anything.
This is the part I think is most underrated: two of the skills (/audit and /level-up) exist specifically to find gaps in the system and ship one improvement per week. It means you're building something that gets better the more you use it.
What do you think? What would you add to a setup like this?
Incredible
What does your AI agent actually do between prompt and response? Now you can see every span, every ms, every guardrail.
4 voted
67%
2 voted
33%
6 votes
Closed
Am upgoating agent trace live
What if your WhatsApp could think, create, and remember—securely?
That’s the vision behind Hamdan AI, my recent project for SAP KSA's side project.
We designed a general-purpose AI assistant that:
• Image Generation & dynamic API calls
• Smart recommendations based on real-time data
• Strict data isolation for both personal and group contexts
And it has 30+ custom tools as well.
Proud of the work that went into making enterprise AI feel this personal.
Check the Full Case Study:
Here
Strong concept and execution, Looking forward to seeing more amazing work from you!
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