Graphext provides a data analytics platform that enables data scientists and business analysts to connect, visualize, and analyze data from multiple sources while creating explainable predictive models using machine learning algorithms. This solution addresses the inefficiencies of traditional dashboards and notebooks by facilitating rapid data exploration and collaboration, allowing users to generate actionable insights in minutes.
Funding
$6.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
EKFPATVFounders
Product
Problem
Traditional data analytics dashboards and notebooks often lack the ability to efficiently connect, visualize, and analyze data from multiple sources, hindering rapid data exploration and collaboration. This can lead to delays in generating actionable insights and building explainable predictive models.
Solution
Graphext is a data analytics platform that enables data scientists and business analysts to connect to various data sources, visualize data instantly, and create explainable predictive models using machine learning algorithms. The platform facilitates deeper exploratory data analysis through AI-assisted correlation analysis and provides interactive visuals for richer data storytelling. Graphext allows users to build and debug predictive models, deploy them instantly, and share insights, streamlining the process from data ingestion to insight generation.
Target Audience
Graphext is designed for data scientists, analysts, and business analysts who need a platform for advanced exploratory data analysis, predictive modeling, and data storytelling.
Features
- Connects to multiple data sources, including BigQuery, Google Cloud Storage, Snowflake, and Microsoft Azure.
- Provides interactive data visualizations and distributions for each variable.
- Offers AI-assisted correlation analysis to discover relationships between variables.
- Enables the creation of presentation-ready visuals for clear communication of findings.
- Facilitates collaboration and sharing of insights between data scientists and business analysts.
- Allows users to build, debug, and deploy predictive models using advanced machine learning algorithms.
- Supports data wrangling functions for cleaning, transforming, and enriching data.