About Scribble Data
Our goal is simple: Empower organizations to solve persistent business problems with data they can trust.
Who are we?
Scribble Data is a feature engineering company for advanced decision analytics. Our intelligence platform, Enrich, enables businesses to make high-impact decisions fast, with reliable and trustworthy data. Our seamless data transformation and pre-built app store frees up valuable time for developers and analysts to focus on critical tasks and collaborate effectively when it comes to solving a multitude of data use cases.

Our Story

Dusty garage origin story 
Sort of. Scribble Data was the second startup for each of the founders. Lots of lessons learnt. Scribble Data was bootstrapped, and eventually revenue helped pay rents, salaries, and for coffee.

Barking up the wrong tree 
We had a product pivot in the early days. Our first product was a natural language data store search interface. Think Google search for your data lake.

What lies ahead for us?
It’s been a hard grift, but Scribble Data’s hit a purple patch now. The engineering rigor we bring to our feature engineering helps customers make better decisions each day. We strive to be known as the last name in robust, trust-inspiring data driven decision-making.
But it hasn’t just been hard grift in the past. It promises to continue in the future as well. We are setting standards in feature engineering, and how companies will use it to power a wide spectrum of high-impact business decisions.
We’re a global company and love to draw people with experiences vastly different from ours, from all sorts of backgrounds, and from everywhere. If curiosity, drive and accountability are part of your fuel, you will do really well with us!
As Seen On
Resources to help you get started

Welcome to the age of Sub-ML use cases
Let’s say you work at a modern data-driven company and you want to find a way to enhance one of your processes, like partner management. It makes sense considering you have limited resources to invest in partner development, but it ranks high on your growth goals for the year. The first step would be to […]
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Hierarchical Features and their Importance in Feature Engineering
Feature engineering is both a central task in machine learning engineering and is also arguably the most complex task. Data scientists who build models that need to be deployed at large scales, across functional, technical, geographic, demographic and other categories have to reason about how they choose the features for the models. Despite the divergent […]
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Growing Data Infrastructure Complexities
The world of data, and data infrastructure, has changed dramatically over the past decade. Traditional databases, which were designed to store information in a structured format, have evolved into massive warehouses of unstructured data that sit on multiple servers across different locations. Not too long ago, we were used to seeing monolithic systems dominated by […]
Read MoreOur Offices

Toronto, Canada

Bangalore, India

New York, United States
... and more, with our team spread across 8 cities across the globe (and counting)!
Reach out to us
For General inquiries:
hello@scribbledata.ioFor Career related inquiries:
careers@scribbledata.ioFor any complaints/grievances:
grievances@scribbledata.io