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Sample build: AI reporting automation for accounting teams. This turns spreadsheet exports, invoice data, and month-end checks into scheduled summaries, exception alerts, and clean review notes.
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’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.
I’ve built something similar for Purchaser, an e-commerce marketplace for automotive and industrial products.
I built a RAG-powered AI agent inside Slack that gives the team access to Purchaser’s product and spare-parts database. Instead of opening Excel and manually searching...
Cozy Cabin — AI Product Commercial
Created this cinematic AI product commercial for Farmhouse Charm Candles, built around their Cozy Cabin Soy Candle.
Cozy Cabin AI Product Commercial
Created this cinematic AI product commercial for Farmhouse Charm Candles, built around their Cozy Cabin Soy Candle.
The goal was...
Good job
I recently designed and developed a complete website through AI. It is live, launched, and already selling a real product.
LOLCRM is an AI-native operating system for venture capital and private equity funds. Its agents research deals, prepare scorecards, draft outreach, and write investment committee documents.
The people behind the fund stay responsible for two actions: supervise and approve.
The difficult part was explaining that system without turning the website into a technical document. A detailed pitch deck already handled capabilities, so the site needed to tell a faster visual story.
A signal enters. An agent gathers context. A draft waits for approval. One click sends the action and updates the deal.
I used AI throughout the design and development process. But I still had to decide what the visitor should understand first, which details belonged in the deck, and how the product should feel to a VC or PE partner.
That is why the site avoids the usual bright SaaS treatment. I chose a dark palette, thin white lines, restrained isometric graphics, and a blueprint-like visual system.
AI did a lot of the production work. It did not decide the narrative, product position, or visual direction.
That distinction matters. A tool can generate another generic landing page in minutes. Someone still has to understand the process, control the style, and know what the product needs to communicate.
For LOLCRM, the output became a working product asset rather than an AI experiment.
@Vladyslav Holdysh The signal-to-agent-to-approval sequence makes the workflow tangible, and the blueprint-like visuals suit the supervision model. Did you test that story with fund partners?