Louvr Performance was built to solve a real problem — too much data, not enough clarity on what to actually do with it. Every recommendation the platform makes is based on how we manage Meta Ads for VALO Gallery. If it wouldn't work on our own budget, it's not in the product.
Get started →Louvr Performance started as an internal tool. We were running Meta Ads for VALO Gallery — a print shop selling hand-illustrated F1 posters — and spending too much time each Monday trying to figure out what to change and what to leave alone.
The problem wasn't access to data. Ads Manager has plenty of data. The problem was the gap between data and decision. We had numbers. We didn't have clarity on what those numbers meant we should do.
So we built a system that pulls campaign data automatically, sends it to Claude AI for analysis, and produces a structured report with three concrete actions. Every Monday at 9am, before the week starts.
The system worked well enough that we opened it to other brands. Louvr Performance is that system, productized.
There are enough tools that show you data. We built something that tells you what to do with it. Every output from Louvr Performance is designed to be acted on that same Monday morning, not filed and forgotten.
Nothing goes into the product unless it works on our own campaigns first. We spend real money on Meta Ads every week. The recommendations are based on what actually moves performance, not marketing theory.
A tool you have to think about how to use is a tool you stop using. Louvr Performance takes under 30 minutes per week. The report arrives automatically. You read it, you act on it, you move on.
No proprietary algorithms. No black boxes. Louvr Performance connects Meta's official Ads API to Claude AI through a Python backend running on Railway. Every piece of the stack is transparent, production-grade, and built to handle real campaign data reliably every week.