The Importance of High-Quality Data in AI Applications

The rise of artificial intelligence (AI) applications has brought about significant advancements in various industries. However, to ensure the success of AI technology, the data used must be of high quality. Seattle-based startup,, aims to address this issue with its innovative data collaboration platform. With $7 million in seed funding, the company offers the first-ever platform that enables software and data/ML developers to build and manage reliable, complete, and accurate data assets. Investors describe as the “GitHub for data” and recognize its potential in revolutionizing the data landscape.

One of the key challenges in AI development is maintaining the quality of data flowing into the applications.’s CEO and co-founder, Chad Sanderson, highlights the absence of effective communication tools for data professionals compared to software engineers who benefit from platforms like GitHub. This communication gap often leads to data quality issues and the subsequent breakdown of AI models. Sanderson draws from his experience leading the data department at Convoy, a digital freight network, where complex data caused trust and quality problems.

Bridging the Communication Gap aims to bridge the communication gap between software engineers and ML developers, thereby improving data quality. Sanderson describes how their platform facilitates collaboration between data producers and data consumers, preventing disruptive changes to critical data workflows. The platform offers data asset recognition, data contract creation, and data contract enforcement, all within the familiar realm of continuous integration/continuous deployment via GitHub. By addressing the communication challenges, enables organizations to enhance data accuracy, reliability, and completeness.’s Impact on AI Scalability

To achieve scalability in AI, it is crucial to overcome communication barriers related to data changes. Sanderson emphasizes the significance of having a change management system for data to scale AI effectively. Large tech companies like Google, Meta, and Amazon rely on extensive teams of data engineers to manage data changes accompanying new machine learning models. However, smaller organizations often lack the resources to employ such teams.’s platform offers a solution by streamlining the process and providing the necessary structure to manage data changes efficiently. has introduced a new category called data contracts, which marks a crucial development in the field of data management. These data contracts act as a fundamental building block for data assets, ensuring their quality and compliance with meaningful constraints. The platform’s innovative approach has garnered significant attention, attracting investments and endorsements from founders of successful data companies like dbt Labs, Monte Carlo, Hex, Kaggle, Hightouch, and Great Expectations. Sanderson’s establishment of the “Data Quality Camp” Slack community further demonstrates the growing interest in these new concepts.

Reshaping the Data Landscape

Apoorva Pandhi, Managing Director at Zetta Venture Partners, acknowledges the potential of’s data contracts in reshaping the data landscape. This emerging data primitive represents a fundamental component of a company’s data stack, alongside other established data management tools. By incorporating data contracts into their workflows, organizations can improve the reliability and accuracy of their AI applications.’s platform is making significant strides in transforming the way data is managed and establishing itself as a key player in the data industry.

In the era of AI, the quality of data is paramount for ensuring the success and reliability of applications.’s innovative data collaboration platform seeks to address the challenges surrounding data quality by bridging the communication gap between software engineers and ML developers. By providing a structured approach to data management, enables organizations to build and manage high-quality data assets effectively. With the emergence of data contracts as a new category in data management, is driving the transformation of the data landscape, earning recognition and support from industry experts. Through its platform, is propelling the development of AI applications to new heights, where data quality is at the forefront of innovation.


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