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July 14, 2020

Datagran Launches First No Code Platform

SAN FRANCISCO, Calif., July 14, 2020 – Datagran, the no code platform that lets developers accelerate time-to-market for their Machine Learning (ML) models by connecting their output to business applications, introduced its flagship platform. Designed to empower developers and growth hackers within data intensive companies, the Datagran platform allows companies to accelerate time-to-market for existing and new products and reduce the total number of tools needed to meet their business goals – without the need to write code and build APIs.

Many companies today are faced with enormous amounts of data they must be able to aggregate and analyze to help them improve sales and operations, reduce churn and increase profitability. The ability to access, understand and use that data effectively can be time consuming and expensive – especially for companies that lack ML and data science expertise. While companies recognize that data is the lifeblood of their business, they also understand that creating the appropriate architecture, running the algos themselves and intelligently and correctly routing the applicable data to the right business application can be incredibly difficult and costly.

The Datagran platform was created to help data savvy developers and growth hackers put business applications into production faster and accelerate their ML models to help sales and business teams boost sales and improve operations. It enables companies to maximize developer resources, lower costs and reduce technical complexity, with no coding required. Datagran clients can enhance collaboration between teams and technologies to ensure they work better together and empower their developers, even those with no ML experience, to easily understand all the data they have and how it powers their critical applications and workflows.

“The current economic climate has placed even more pressure on businesses to control costs, maximize resources and quickly launch new value-add products to market – but they cannot do that if they lack the technical savvy and skillset to read, organize and analyze their data,” said Carlos Mendez, CEO, Datagran. “The Datagran platform gives our clients the power and benefits of data science they need to strengthen their existing development teams and allow them to create the machine learning models they need themselves, without additional coding and without having to go outside the team for support. Our team has been focused on machine learning since our inception, and we continue to work closely with our clients to provide them the functionality they need to easily harness the power of their data to improve their algorithms and feed their most critical business applications.”

Datagran’s simple to use drag and drop features eliminate manual processes and the need for developers to write their own algorithms, code or APIs to connect different tools and applications, significantly reducing cost and time and increasing the lifetime value of those applications. The company has also introduced Datagran Academy, an online educational academy to help Datagran clients who are not machine learning experts or data scientists understand how to use the Datagran platform to easily deploy their own algorithms.

The Datagran platform is currently available. For more information, please visit https://www.datagran.io/.

About Datagran

Datagran empowers developers and growth hackers to connect business applications, run machine learning (ML) models and automate workflows with no coding required. Some of the world’s largest brands use our no code platform to accelerate time to market for new products, reduce technical complexity and enhance team collaboration. Our drag and drop features allow companies to easily share, organize and analyze data and connect the output to the right business applications. Founded by ML experts, Datagran allows companies to lower costs, reduce the number of tools they use and deploy fewer resources while meeting their business goals.


Source: Datagran 

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