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Sambath Kumar Natarajan
Sambath Kumar Natarajan

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I built a Collaborative Data Canvas to end " Multiple spreadsheet sharing issue"

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

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