Graphext raised $4.6M to create the best exploratory data analysis platform for building explainable AI models

June 6, 2023
Data News
Victoriano Izquierdo
Victoriano Izquierdo

TLDR: We are excited to share that Graphext has just closed a $4.6M seed round, lead from Hoxton and 80 angels, bringing our total seed funding to $7M.

From spreadsheets to dashboards, from notebooks to Graphext. From business analysts to data scientists.

First came spreadsheets for crunching numbers for accounting and financial planning. Then BI platforms to visualize KPIs and CRM data in dashboards. And for the past few years, we have seen the emergence of Jupyter Notebooks to analyze why these KPIs changed (or not) and make predictions about churn, lead scoring, product recommendations, and other advanced analysis. 

With digitization, companies started gathering more and more data, allowing them to move from intuition to science. Ten years ago, only 6K “data scientists” were listed on Linkedin; now, there are over 600K. The growth of data scientists is expected to continue annually in double digits. 

A powerful mix of design and engineering for the era of AI.

Modern data scientists deserve new interfaces to enjoy more their work interacting with data. These interfaces should be far more sophisticated than spreadsheets and dashboards yet more intuitive and powerful than notebooks.

Great data scientists are artists, and data science is very visual by nature. They write lots of code for data transformations, plotting charts, and putting models in production. This is because it's technologically challenging to build the tools they need. Imagine you want a tool as interactive as Figma, but for data science instead of product design. You would have to create new technology as they did. Over the last 6 years, we've been doing just that.

We've squeezed new tech standards like Webassembly, WebGL, and Apache Arrow. We've also created our own unique libraries for working with millions of rows on the browser and orchestrate pretty efficiently complex data pipelines on the backend. We have even created our own low-code language. All this effort wasn't just to slightly improve tools like Jupyter Notebooks. We wanted to create something truly new and significantly better.

What is Graphext?

Graphext is a data exploration and predictive modeling platform that enables Data Scientists to explore data, create predictive models and collaborate with the business in a single place.

Graphext can connect with, read, and write data from any modern data warehouse. This includes Snowflake, Google Bigquery, Databricks, Redshift, Azure, and others. It can even work with simple data sources, like an Excel file, a CSV, Google Sheets, or even a Notion database.

Once connected, you can begin to dive into your data. You can group similar variables together and understand how they are correlated using cross-filters. From a date, you can figure out the day of the week or whether it was a holiday. You can guess a person's gender from their name. You can enrich the data with census information if you have someone's address. 

If you want to get more advanced, you can do things like unsupervised clustering or topic modeling for text. Create embeddings for images. You can find out what makes two segments of customers different. And finally, you can create a model and use it to make predictions for things like lead scoring or customer churn and explain the model.  

We firmly believe that the best tool for creating explainable predictive models is also the best tool for exploring data.

Team, Traction, and Investment

At Graphext, our journey has been focused on investing in technology. We’re a team of great Designers, Engineers, and Data Scientists, and we’ve invested heavily in creating product for the Data Science community. We are very proud of this team and what they have been able to accomplish so far. We’re all on a mission to create an advanced and intuitive platform that every Data Scientist loves to use.

Currently, we have more than 10K users and 80 paying customers. This goes even further when we look at the number of Data Science education programs integrating Graphext into their curriculum.

We decided to partner with Hoxton because of their Silicon Valley mindset. This will be key to continuing our growth in the United States. Our new board members, Charles Seely (Hoxton), Bernardo Hernández (Flickr, Google, Idealista) and Miguel Martínez (Signal AI co-founder and former Chief Data Scientist) will be instrumental in achieving this goal. They both have a lot of experience in the US and the UK, creating great companies where design and technology are the key factors. 

Finally, I would like to thank our Angels. We've been fortunate to have the backing of several people that understand our industry so well, great entrepreneurs, managers, and individual contributors like:

Miguel Arias (former COO at CARTO & partner at Kfund) 

Taimur and Lukas (Founders of Causal)

Serhii Sokolenko (Product at Snowflake)

Juan Luis Pérez (former Global Head of Research at UBS)

Joaquin Cuenca, Alejandro, and Pablo Sánchez (founders of Freepik)

Vicent Martí (GitHub, Planetscale)

Javi Lopez (Founder of Erasmusu) 

Juanjo Mostazo (Co-founder and CTO of Homa Games)

Ahmed Men (Founder of

Peter Borders (Trayectory Ventures)

Jose Florido (Spotify, Meta, Google), among many others angels. 


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