The Problem: The "Final_V12_updated.xlsx" Nightmare
We’ve all been there. You have a critical business decision to make, but the data is trapped in five different CSVs, three email threads, and a "static" dashboard that was last updated two weeks ago.
I spent months watching brilliant analysts get bogged down in VLOOKUPs and manual joins just to answer simple questions like, "Why is our LTV dropping?"
I decided to build a solution that treats data analysis like Figma: collaborative, instant, and visual.
Introducing AUM Data Labs
AUM Data Labs isn’t just another BI tool. It’s a Collaborative Canvas designed for speed.
The Technical Moat: Domain-Aware Analysis
The core of the platform is a Python-based Domain Engine. Instead of forcing users to write SQL or complex form…
The Problem: The "Final_V12_updated.xlsx" Nightmare
We’ve all been there. You have a critical business decision to make, but the data is trapped in five different CSVs, three email threads, and a "static" dashboard that was last updated two weeks ago.
I spent months watching brilliant analysts get bogged down in VLOOKUPs and manual joins just to answer simple questions like, "Why is our LTV dropping?"
I decided to build a solution that treats data analysis like Figma: collaborative, instant, and visual.
Introducing AUM Data Labs
AUM Data Labs isn’t just another BI tool. It’s a Collaborative Canvas designed for speed.
The Technical Moat: Domain-Aware Analysis
The core of the platform is a Python-based Domain Engine. Instead of forcing users to write SQL or complex formulas, the engine uses proprietary logic to:
Auto-Detect Domains: It identifies if you’ve uploaded E-Commerce, SaaS, or Biotech data.
Instant Diagnosis: It runs benchmarked KPIs (GMV, Conversion Rate, etc.) and flags anomalies instantly.
Secure Formula Evaluation: We built a custom evaluator to ensure that while the logic is flexible, the environment remains secure against injection.
Key Features I’m Proud Of:
Visual Join Builder: Drag and drop columns to link messy datasets without a single line of code.
Real-time Collaboration: Built with a custom sync layer, you can see your teammate’s cursors moving across the canvas as you investigate together.
Natural Language Querying: Ask "Show count of orders by category" and watch the chart render in real-time.
The Architecture
Frontend: React with a custom-built canvas engine for high-performance data manipulation.
Backend: FastAPI (Python) orchestrating the heavy lifting of the analytical engines.
State: Real-time synchronization for multi-user collaboration.
Why I Built This
I built AUM Data Labs during a period of intense professional transition. I wanted to prove that you can build enterprise-grade technical excellence without a massive team.
My Goal: To make high-level data diagnosis accessible to the people who actually make the decisions—Product Managers, Founders, and Ops Leads—not just the people who write the SQL.
I Need Your Brutal Feedback!
I’m launching the Free Tier (2-Editor limit) today. I would love for this community to try and break it.
Drop your messiest CSV.
Try the Visual Join.
Ask the NL bar a complex question.
Check it out here: https://www.aumdatalabs.com/signup Demo: https://youtu.be/JdDpRe8Lzbs